OpenAI's Deep Research Sparks Open-Source Rivalry: Hugging Face Replicates Tool in 24 Hours

Researchers Replicate OpenAI's Hot New AI Tool in 24 Hours

AI developer Hugging Face says it's created an open-source AI research agent that can trade blows with OpenAI's latest Deep Research feature -- in just 24 hours. The Sam Altman-led company released the agent, which "uses reasoning to synthesize large amounts of online information and complete multi-step research tasks for you," over the weekend. Simply put, Deep Research -- the company technically doesn't capitalize the name, but we're just going to go ahead and do so because it looks bizarre not to -- sits on top of an existing AI model to provide new functionality to the user. In practice, you can ask it to do things like generate a "competitive analysis on streaming platforms or a personalized report on the best commuter bike," according to OpenAI, which could take "anywhere from five to 30 minutes." But it didn't take long for Hugging Face researchers to come up with a worthy alternative. "While powerful LLMs are now freely available in open-source, OpenAI didn't disclose much about the agentic framework underlying Deep Research," Hugging Face wrote in a Tuesday announcement. "So we decided to embark on a 24-hour mission to reproduce their results and open-source the needed framework along the way!" The company created an "agent" framework" that writes actions in code instead, which it says immediately led to a major bump in performance. It's not perfect quite yet, it's worth pointing out. Hugging Face's Open Deep Research scored a 55.15 percent accuracy on a benchmark called General AI Assistants, while OpenAI's version scored 67.36, leaving some room for improvement. (OpenAI's version itself still has a lot of trouble distinguishing between "information from rumors," greatly undercutting its current usefulness as a research analyst.) But considering that Hugging Face, which has far fewer resources to work with than OpenAI, created its agent in a mere 24 hours, the challenge highlights just how replaceable OpenAI's AI tools have become. Every time it drops a hot new AI, there now seems to be a race to duplicate its capabilities with a fraction of the gigantically funded company's resources. While Hugging Face's Aymeric Roucher, who led the research, told Ars Technica that the agent "worked well" with OpenAI's o1, he added that Hugging Face's open-source model called open-R1 may soon work even "better." The exchangeability of AI models is an especially pertinent topic, considering the emergence of Chinese AI startup DeepSeek, which upended the entire tech sector with its extremely lean and efficient model called R1 last month. (Hugging Face's open-R1 is an open source version of DeepSeek's model). DeepSeek also likely flexed the power of distillation, which is the strategy of creating "reasoning" capabilities by training an AI model on the output of another one. Whether that constitutes any violation of intellectual property, something that OpenAI has since accused DeepSeek of doing, remains to be seen, especially considering OpenAI's own AI was built by indiscriminately ripping off protected content on the internet. But it's a clever workaround that could give AI industry stalwarts like OpenAI a run for their money. Case in point, researchers at Stanford and the University of Washington developed a worthy rival to OpenAI's o1 "reasoning" model for less than $50 worth of cloud compute credits, as detailed in a yet-to-be-peer-reviewed paper that was first spotted by TechCrunch. That new model, dubbed s1, performed on the level of DeepSeek's R1 and OpenAI's o1 on math and coding tests. It was distilled using the output of Google's (mostly) free-to-use Gemini 2.0 Flash Thinking Experimental reasoning model. The team trained s1 using a dataset of just 1,000 curated questions with answers from Google's AI. It took less than 30 minutes to achieve strong performance on AI benchmarks, as TechCrunch reports, using a mere 16 Nvidia AI chips. Meanwhile, the industry's biggest players like OpenAI and Meta are planning to pour hundreds of billions of dollars into initiatives to expand AI infrastructure in the US, enormous investments that were thrown into question by the emergence of much cheaper to train and run alternatives like DeepSeek. Whether these tools can ever even turn a profit, let alone stop hallucinating facts every step of the way, remains as uncertain as ever -- especially when the little guys can quickly clone their best work and offer it for free.

Save $200/Month: The Open Source Alternative to OpenAI Deep Research

OpenAI's "Deep Research" tool has emerged as a sophisticated solution for generating detailed, citation-backed research. However, its high subscription cost has driven many users to explore open source alternatives that offer similar functionality at a fraction of the price. NetworkChuck provides a comprehensive comparison of OpenAI's tool against a much cheaper open source alternative, focusing on their features, usability, and performance in automating advanced research tasks. A tool that claims to rival OpenAI's capabilities while keeping costs low and control in your hands. With a bit of technical know-how, this option opens the door to advanced research features without the hefty subscription fee. Learn how these two AI tools stack up, exploring their strengths, limitations, and the surprising ways they can simplify your research process. Have you ever found yourself stuck in the middle of a research project, wishing there was a faster, smarter way to gather reliable, citation-backed information? Whether you're a student racing against a deadline, a professional preparing a detailed report, or just someone curious about a complex topic. Open source alternatives might be the answer. OpenAI's Deep Research tool uses the advanced capabilities of the GPT-3.5 model to perform complex, multi-step reasoning tasks. It is designed to process a variety of data formats, including text, images, and PDFs, and delivers comprehensive, citation-supported research in a matter of minutes. Its standout features include: Despite these strengths, the tool's $200/month subscription fee via ChatGPT Pro presents a significant financial barrier, particularly for individual users and smaller organizations. This cost factor has led many to consider alternative solutions. In response to the financial limitations of OpenAI's tool, an open source alternative has gained traction. This option replicates many of the core functionalities of Deep Research while offering greater transparency and control over the research process. Key features of the open source tool include: While the open source tool eliminates subscription fees, it requires a degree of technical expertise for installation and operation. This makes it less accessible to non-technical users who may prioritize ease of use. Uncover more insights about OpenAI Deep Research in previous articles we have written. Both OpenAI's Deep Research and the open source alternative use the GPT-3.5 model, making sure high-quality research outputs. However, their differences in usability, flexibility, and performance are significant: The decision between these tools ultimately depends on individual priorities. Users seeking convenience and ease of use may prefer OpenAI's solution, while those prioritizing cost-effectiveness and control may find the open source option more appealing. For those interested in the open source alternative, setting it up involves a straightforward but technical process. Follow these steps to get started: While the setup process requires some technical proficiency, it unlocks powerful research capabilities without the high subscription costs associated with OpenAI's Deep Research. Both OpenAI's Deep Research and the open source alternative excel in generating detailed, citation-backed research. Their real-world applications span a variety of fields, including academic research, market analysis, and content creation. For instance, when tasked with exploring topics such as "the benefits of renewable energy" or "emerging trends in artificial intelligence," both tools delivered nuanced, data-driven insights. However, key differences emerged: These distinctions highlight the trade-offs between ease of use and affordability, helping users determine which tool aligns better with their specific needs and resources. The development of AI-driven research tools is advancing rapidly, with open source platforms like Hugging Face leading the charge in providing widespread access to access to advanced AI capabilities. These initiatives aim to provide robust alternatives to proprietary solutions like OpenAI's Deep Research. As competition grows, users can anticipate several key trends: This ongoing innovation is expected to make AI-driven research tools more accessible and practical for a broader audience, from individual researchers to large organizations. Learn more about the Open Deep Research open source alternative over on Github.

Don't want to pay for ChatGPT Deep Research? Try this free open-source alternative

Also: Why Mark Zuckerberg wants to redefine open source so badly Just two days after OpenAI announced Deep Research, a new AI agent within ChatGPT that can sift through online sources for you, its open-source counterpart has already emerged. On Tuesday, Hugging Face released its equivalent to the new feature. Blatantly dubbed open Deep Research, the alternative uses OpenAI's o1 model and an agentic framework to navigate the web. The open alternative achieved 55% accuracy on the General AI Assistants benchmark (GAIA), a top assessment test for agents, compared to Deep Research's 67%, and ranks in first place for open submissions. However, Hugging Face acknowledged the agent is not yet a full competitor to OpenAI's. "Deep Research is a massive achievement and its open reproduction will take time," the developer platform said in a blog titled "Freeing Our Search Agents." "In particular, full parity will require improved browser use and interaction like OpenAI Operator is providing, i.e. beyond the current text-only web interaction we explore in this first step." OpenAI's Deep Research is underpinned by a version of its latest and most advanced reasoning model, o3, of which there is currently no known open-source equivalent. According to OpenAI's blog, this model version also outperformed top models on Humanity's Last Exam , a new AI benchmark test released just last week, and is much more challenging than other popular tests, with a "new high" of nearly 27% accuracy. Also: Jailbreak Anthropic's new AI safety system for a $15,000 reward That said, HLE's creators point out a potential "contamination": o3 was evaluated after HLE was released, meaning OpenAI had access to its prompts. Hugging Face did not mention whether it had tested open Deep Research on HLE. To better compete, the platform says it's building "agents that view your screen and can act directly with mouse & keyboard." Considering its $200-per-month price tag via ChatGPT Pro, Deep Research may be inaccessible to most. If you want to try something similar for free, check out open Deep Research's live demo here, which Hugging Face refers to as a "simplified version" of the full agent. Also: Are ChatGPT Plus or Pro worth it? Here's how they compare to the free version The pace at which Hugging Face was able to create something of a competitor -- under 24 hours -- marks the race that makers of proprietary models increasingly find themselves in. Researchers at UC Berkeley made a model comparable to o1-preview in just 19 hours earlier last month. DeepSeek's exact timeline on R1, its o1 rival model, is unknown, but it is understood to be lower-resource in terms of time and spend.

After 24-hour hackathon, Hugging Face's AI research agent nearly matches OpenAI's solution

On Tuesday, Hugging Face researchers released an open source AI research agent called "Open Deep Research," created by an in-house team as a challenge 24 hours after the launch of OpenAI's Deep Research feature, which can autonomously browse the web and create research reports. The project seeks to match Deep Research's performance while making the technology freely available to developers. "While powerful LLMs are now freely available in open-source, OpenAI didn't disclose much about the agentic framework underlying Deep Research," writes Hugging Face on its announcement page. "So we decided to embark on a 24-hour mission to reproduce their results and open-source the needed framework along the way!" Similar to both OpenAI's Deep Research and Google's implementation of its own "Deep Research" using Gemini (first introduced in December -- before OpenAI), Hugging Face's solution adds an "agent" framework to an existing AI model to allow it to perform multi-step tasks, such as collecting information and building the report as it goes along that it presents to the user at the end. The open source clone is already racking up comparable benchmark results. After only a day's work, Hugging Face's Open Deep Research has reached 55.15 percent accuracy on the General AI Assistants (GAIA) benchmark, which tests an AI model's ability to gather and synthesize information from multiple sources. OpenAI's Deep Research scored 67.36 percent accuracy on the same benchmark. As Hugging Face points out in its post, GAIA includes complex multi-step questions such as this one: Which of the fruits shown in the 2008 painting "Embroidery from Uzbekistan" were served as part of the October 1949 breakfast menu for the ocean liner that was later used as a floating prop for the film "The Last Voyage"? Give the items as a comma-separated list, ordering them in clockwise order based on their arrangement in the painting starting from the 12 o'clock position. Use the plural form of each fruit. To correctly answer that type of question, the AI agent must seek out multiple disparate sources and assemble them into a coherent answer. Many of the questions in GAIA represent no easy task, even for a human, so they test agentic AI's mettle quite well.

OpenAI Responds to DeepSeek Hype with 'Deep Research' ChatGPT Agent - Decrypt

Artificial intelligence firm OpenAI has launched Deep Research, a new AI-powered agent within ChatGPT that independently conducts in-depth web research, analyzes data, and compiles reports -- completing tasks that would take humans hours or even days. The tool, available now for Pro users, is designed for professionals in finance, science, policy, and engineering, as well as anyone looking for "thorough, precise, and reliable research," according to OpenAI's Feb. 2 announcement. The release comes at a time of growing competition in AI research, with China-based DeepSeek flipping the script on AI economics, claiming it can match ChatGPT's intelligence without the heavyweight price tag. OpenAI CEO Sam Altman hyped the tool on Twitter, calling it "like a superpower; experts on demand!" Altman shared a personal use case where Deep Research helped him find a rare NSX car in Japan after he had nearly given up searching manually. Users can access Deep Research by selecting it in ChatGPT's message composer, inputting a query, and attaching files or spreadsheets for additional context. The AI then analyzes hundreds of sources over five to 30 minutes, displaying a sidebar tracking its research process before delivering a fully cited report. Despite its advanced capabilities, Deep Research isn't without its quirks. OpenAI concedes that the model "can sometimes hallucinate facts or make incorrect inferences" and struggles with differentiating authoritative sources from misinformation. Currently, Pro users can access 100 queries per month, with Plus and Team users expected to get access next, followed by Enterprise customers. OpenAI is reportedly working on a faster, more cost-effective version to increase query limits for paid users. To bolster its case, OpenAI pointed to Deep Research's performance on Humanity's Last Exam, an AI benchmark testing expert-level knowledge across 100+ fields. Deep Research's o3 model scored 26.6% accuracy, far surpassing DeepSeek-R-1's 9.4% and even OpenAI's GPT-4o, which managed only 3.3%. The timing of OpenAI's launch is no coincidence -- last December, Google rolled out its own "Deep Research" feature for its Gemini AI model for Gemini Advanced users. The AI giants are now locked in a battle to define the future of AI-driven, autonomous knowledge discovery -- a far cry from the chatbot era that started it all.

OpenAI Debuts Tool to Conduct 'Deep Research' Online | PYMNTS.com

OpenAI has debuted an AI tool dubbed "deep research" capable of performing multi-step online research. "It accomplishes in tens of minutes what would take a human many hours," the company wrote in its Sunday (Feb. 2) announcement. "Deep research is OpenAI's next agent that can do work for you independently -- you give it a prompt, and ChatGPT will find, analyze and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst." According to the company's announcement, deep research is powered by an iteration of OpenAI's upcoming o3 artificial intelligence (AI) model that is designed for web browsing and data analysis. When prompted by users, the company's ChatGPT chatbot will find, analyze and synthesize online sources like images, text and PDF to create a report. OpenAI says this tool is designed for people doing "intensive knowledge work" in fields like finance, engineering and policy, though it can also be useful for "discerning shoppers looking for hyper-personalized recommendations" for products requiring research like cars or appliances. OpenAI also noted that deep research is a work in progress and has its limits, and that the tool "may struggle with distinguishing authoritative information from rumors, and currently shows weakness in confidence calibration, often failing to convey uncertainty accurately." The announcement follows news from this weekend that OpenAI was reconsidering its shift to a closed-source development approach. This rethink comes after DeepSeek's release of a lower cost open-source AI model, executives said during a Reddit "Ask Me Anything" event last week. OpenAI CEO Sam Altman said during the event that his company needs to "figure out a different open-source strategy." Altman added that not everyone at OpenAI shares that view and that figuring out the strategy is "not our current highest priority," per a Seeking Alpha report. News about DeepSeek shook both Wall Street and Silicon Valley last week, with the Chinese company's model appearing to perform the same functions as many American AI models at a sliver of the cost. "Artificial intelligence has reached a critical inflection point. The industry stands at a crossroads where escalating costs, environmental concerns, and innovation appear intertwined, threatening to stifle accessibility and adoption," Gokul Naidu, a consultant for SAP, told PYMNTS last week. "Enter DeepSeek-R1, the model that's turning heads in Silicon Valley and beyond for proving that high performance and affordability aren't mutually exclusive."

OpenAI's Latest Agent Promises 'Deep Research' in Minutes

Called "Deep Research," the AI agent runs on a version of OpenAI's upcoming o3 model. It can "find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst," OpenAI says. The tool is built for people who do "intensive knowledge work in areas like finance, science, policy, and engineering and need thorough, precise, and reliable research." At launch, it is available on the web for ChatGPT Pro subscribers ($200 per month), who can submit up to 100 queries a month. To get started, eligible users can click the new Deep Research button in the message box and enter a prompt. In addition to text, users can add files or spreadsheets to provide the AI agent with better context. Once it starts working, ChatGPT will open a sidebar summarizing the steps it takes and the sources used. Depending on the query, the tool might need five to 30 minutes to complete the task. After that, it will notify the user and provide them with a report in the chatbox. "Every output is fully documented, with clear citations and a summary of its thinking, making it easy to reference and verify the information," OpenAI said, adding that the tool "accomplishes in tens of minutes what would take a human many hours." Currently, the reports are text-only, but in the next few weeks, OpenAI will add embedded images, data visualizations, and other analytic outputs to improve clarity. On Humanity's Last Exam, a recently released benchmark that evaluates the reasoning abilities of AI models, OpenAI's Deep Research returned with 26.6% accuracy. In comparison, DeepSeek's R1 model stands at 9.4%, and Google's Gemini Thinking stands at 6.2%. Interestingly, Google launched a similar tool with the same name last year for Gemini Advanced subscribers ($20 per month). One big advantage of Google's model is that it lets users export the final report to Google Docs. OpenAI warns that its Deep Research tool might hallucinate. Users will also find "minor formatting errors in reports and citations" at launch, making it important to verify the provided information before taking any significant action. While the AI agent is currently available to ChatGPT Pro users on the web, OpenAI expects to roll it out to mobile and desktop apps by the end of this month. As part of the staggered rollout, ChatGPT Plus and Team subscribers will receive it next, followed by Enterprise. Deep Research's announcement comes just over a week after OpenAI launched "Operator," an AI agent that can automate web-based tasks like planning trips, ordering groceries, etc.

OpenAI's new Deep Research agent can do in 5 minutes what might take you hours

What's better than an AI chatbot that can assist you with tasks? One that can do them for you. OpenAI continues to build out its AI agents in ChatGPT with the launch of Deep Research. On Sunday, OpenAI unveiled Deep Research, an AI agent that can conduct multi-step research for you by pulling a robust amount of information from the web and synthesizing those sources for you in a comprehensive report. Once prompted, Deep Research can work entirely independently; it's like having a research analyst at your command. Powering Deep Research is a version of the OpenAI o3 model optimized for web browsing and data analysis. By leveraging o3's advanced reasoning capabilities, it can search and interpret massive amounts of content from the web, including texts, images, and more, and then output it in a report targeted to your needs. Each report is generated in five to 30 minutes, depending on the task at hand. However, you can work on other tasks during that time, optimizing your workflow productivity. The finished report is output in the chat. In the weeks to come, the agent will also include images, data visualizations, and more. Also: How Gen AI means better customer experiences - see one bank's approach According to OpenAI, the same work would take humans hours. Furthermore, the agent is meant to be particularly good at finding niche information that would require humans to perform multiple searches. According to OpenAI, the target audience for Deep Research includes those who do intensive knowledge work in finance, science, policy, and engineering -- and who need reliable, thorough research. Every report includes clear citations and a summary of the agent's thinking so that users can double-check the information for themselves. Double-checking a chatbot's responses is generally good practice, as chatbots are prone to hallucinations. In particular, OpenAI warns that Deep Research "can sometimes hallucinate facts in responses or make incorrect inferences, though at a notably lower rate than existing ChatGPT models, according to internal evaluations." OpenAI also added that the agent can struggle to distinguish authoritative information from rumors and can fail to convey uncertainty correctly, highlighting the need for human review. In the blog post announcing the feature, OpenAI includes the same side-by-side results of GPT-4o versus Deep Research to showcase how the same prompt generates very different results. The ones generated with Deep Research were much more robust and better organized. Deep Research also outperformed GPT-4o on Humanity's Last Exam, a recently launched AI benchmark exam by Scale AI and the Center for AI Safety (CAIS) that tests various subjects on expert-level questions. Deep Research scored a 26.6% accuracy, outperforming GPT-4o, Grok-2, Claude 3,5 Sonnet, Gemini Thinking, o1, and even o3-mini high, which had just scored the highest score a couple of days prior, as highlighted by OpenAI CEO Sam Altman. OpenAI also published Deep Research's performance results on a series of other evaluations, including GAIA⁠, a public benchmark that evaluates AI on real-world questions and an internal evaluation of expert-level tasks across different areas of deep research. In both, Deep Research had impressive results, even topping the GAIA external leaderboard. Because of the computing power required to run the Deep Research feature, only ChatGPT Pro users can access it at the moment. The $200-per-month subscription includes access to up to 100 queries of an optimized version and other perks such as unlimited access to ChatGPT and Sora and access to Operator, its AI agent feature that can carry out basic browser tasks like reservations. ChatGPT Plus and Team users will get access next, followed by Enterprise and then free users. OpenAI shares that it plans to release a faster, more cost-effective version of the feature powered by a model that is smaller but just as efficient. Also: How Gen AI means better customer experiences - see one bank's approach If you want access to the feature now but don't want to shell out the $200 per month, Google has a similar feature, also called Deep Research, that is available to all of its Gemini Advanced users through the Google One AI Premium plan that costs $20 per month. Back in December, Altman even replied to an X user who asked Altman to "do a deep research feature like Gemini but better," with "kk," suggesting that the newly released Deep Research feature is OpenAI's answer to Google. Last week, Microsoft also announced a feature capable of more thorough reasoning called Think Deeper, which allows users to leverage OpenAI's O1 reasoning model to deliver higher-quality responses to complex prompts. However, unlike Gemini and OpenAI's Deep Research features, it doesn't have agentic capabilities or access to the internet. The biggest perk is that the experience is entirely free.

OpenAI launches 'deep research' tool that it says can match research analyst

ChatGPT developer announces AI agent amid growing challenge from rivals such as China's DeepSeek OpenAI has stepped up its development of artificial intelligence agents by announcing a new tool that crafts reports which it claims can match the output of a research analyst. The ChatGPT developer said the new tool, "deep research", "accomplishes in 10 minutes what would take a human many hours". The announcement comes just a couple of days after the San Francisco-based company said it would speed up product releases in response to advances made by OpenAI's Chinese rival DeepSeek. Deep research is an AI agent - the term for a system that can carry out tasks on users' behalf - and is powered by a version of OpenAI's latest cutting-edge model, o3. OpenAI said deep research would find, analyse and synthesise hundreds of online sources to create a "comprehensive report", sifting through "massive amounts" of text, images and PDFs to do so. The company said its tool, which will be available as a button in ChatGPT, is a "significant step" towards its goal of developing artificial general intelligence, a theoretical term referring to systems that match or exceed humans at any intellectual task. Last month OpenAI announced Operator, an AI agent that it claims can book a table at a restaurant or carry out an online shop based on a photo of a shopping list - but is only available in a preview version in the US. In a demo video released on Sunday, OpenAI showed deep research analysing the market for translation apps. The company said the tool will take between five and 30 minutes to complete each task and will cite the source for each claim it makes. OpenAI said deep research was for professionals who work in areas such finance, science and engineering, but it can also examine purchases such as cars and furniture. It is based on o3, OpenAI's latest "reasoning" model, which takes longer to process queries than conventional models and has yet to be released in full publicly. It comes after OpenAI announced the release on Friday of another derivation of o3 - a free slimmed-down version called o3-mini. The power of the full o3 model was flagged in the International AI Safety Report published last week. The study's lead author, Yoshua Bengio, said its capabilities "could have profound implications for AI risks". He said o3 had surprised experts, including himself, with its performance in a key abstract reasoning test. Deep research will be available in the US for users of OpenAI's Pro tier - which costs $200 (£162) a month - but at a limit of up to 100 queries a month, reflecting the cost of processing every query under the tool. It is not available in the UK and Europe. Andrew Rogoyski, a director at the Institute for People-Centred AI at the University of Surrey, said there was a danger that humans could use outputs from tools like deep research verbatim and not carry out retrospective checks on what they produce. "There's a fundamental problem with knowledge-intensive AIs and that is it'll take a human many hours and a lot of work to check whether the machine's analysis is good," Rogoyski said.

How OpenAI's Deep Research Agentic AI is Changing Online Research

OpenAI's new "Deep Research" represents a significant advancement in artificial intelligence (AI), using the capabilities of the o3 language model to address complex research tasks. This latest AI research system is particularly adept at retrieving obscure knowledge and handling nuanced queries, making it a valuable tool for researchers, academics, and professionals, and may take anywhere from 5 to 30 minutes to complete its web crawl. Despite its strengths, it faces notable challenges, including hallucinations, over-reliance on clarifying questions, and occasional inaccuracies. In this overview the AI Explained teams, looks deeper into what makes Deep Research stand out, exploring its impressive capabilities and the areas where it still falls short. Whether you're a professional looking to streamline your workflow or simply curious about the future of AI in research, this tool offers a glimpse into how technology is reshaping the way we process and analyze information. But don't worry -- we're not here to overwhelm you with technical jargon. Instead, we'll break it all down, so you can decide if Deep Research is the right fit for your needs or just another step in AI's ever-evolving journey. Deep research is built for people who do intensive knowledge work in areas like finance, science, policy, and engineering and need thorough, precise, and reliable research. It is particularly effective at finding niche, non-intuitive information that would require browsing numerous websites. Freeing up valuable time by allowing you to offload and expedite complex, time-intensive web research with just one query. Designed to tackle the most complex research tasks, this innovative AI tool from OpenAI promises to make obscure knowledge retrieval and nuanced queries more accessible than ever. Deep Research is purpose-built to manage intricate research tasks with precision, offering significant utility for users seeking detailed or hard-to-find information. Powered by OpenAI's o3 model, the system demonstrates advanced capabilities in processing complex queries and analyzing extensive datasets. Key features include: However, the system struggles with tasks requiring spatial reasoning and common-sense decision-making. These limitations highlight areas where human cognition continues to outperform AI, emphasizing the need for complementary human-AI collaboration. Deep Research has demonstrated significant progress compared to earlier AI models. For example, its performance on the GUIA benchmark improved from 15% to 72%, showcasing its ability to handle complex research scenarios. This improvement underscores its potential to transform how researchers and professionals approach data-intensive tasks. One of its defining characteristics is the frequent use of clarifying questions. While these questions often enhance the accuracy of its responses, they can slow down workflows for users who prioritize speed and simplicity. Additionally, hallucinations -- instances where the AI generates incorrect or fabricated information -- remain a critical issue, particularly in high-stakes applications such as healthcare or legal research. Advance your skills in AI research by reading more of our detailed content. When compared to other AI tools, Deep Research exhibits both notable strengths and areas for improvement: These comparisons highlight the system's potential while also emphasizing the need for further refinement to address its limitations. Deep Research excels in several specialized applications, making it a versatile tool for professionals and researchers. Key use cases include: Despite these strengths, the system's limitations become evident in real-world scenarios. For instance, it struggles with tasks requiring high accuracy, such as price history research or providing shopping advice. Its tendency to hallucinate further reduces its reliability in critical fields like healthcare, legal research, or financial analysis, where errors can have significant consequences. The advancements demonstrated by Deep Research signal a potential shift in traditional white-collar roles, particularly those involving repetitive or data-intensive tasks. As the system becomes more reliable, it could reduce the need for human involvement in certain areas, streamlining workflows and increasing efficiency. However, its current limitations suggest that human oversight will remain essential in the near term. The broader societal implications of such technologies raise important questions about the future of work and human-AI collaboration. Tools like Deep Research have the potential to accelerate technological progress and reshape the global economy, but they also introduce ethical and practical challenges. Issues such as data privacy, algorithmic bias, and the displacement of human labor must be carefully addressed to ensure responsible AI development. Access to Deep Research is structured through a subscription-based model, with pricing tiers designed to accommodate different user needs: Users in Europe face additional challenges, as a VPN is required to access the service. The system's interface is designed to prioritize detailed outputs, often incorporating clarifying questions to refine results. While this approach enhances accuracy, it may frustrate users who prefer more straightforward interactions or faster results. The GUIA benchmark highlights the significant progress made by Deep Research, particularly in handling complex research scenarios. However, it also reveals areas where human capabilities still surpass AI. For example, the system struggles with benchmarks like Simple Bench and Code Elo, which test fundamental reasoning and coding skills. In practical applications, its performance is mixed. While it excels in tasks such as language analysis and obscure knowledge retrieval, it falls short in providing reliable shopping advice or solving spatial reasoning challenges. These results underscore the need for ongoing development to address its weaknesses and expand its utility. The rapid pace of AI innovation suggests that tools like Deep Research could soon surpass human capabilities in specific areas. However, its current limitations -- particularly in managing hallucinations and making sure accuracy -- remain significant barriers to widespread adoption for critical tasks. As AI systems continue to evolve, their societal impact will grow. Questions surrounding the ethics of human-AI collaboration, the future of employment, and the pace of technological progress will remain central to discussions about artificial intelligence. While Deep Research represents a step forward, its development also underscores the importance of balancing innovation with responsibility, making sure that advancements in AI benefit society as a whole.

OpenAI's $200 deep research will write reports for you but is it worth it?

OpenAI has introduced a new artificial intelligence tool named deep research that conducts extensive online research for users, addressing tasks ranging from complex scientific inquiries to personalized product recommendations. The service is available to paying customers through OpenAI's ChatGPT chatbot. Deep research can generate comprehensive reports in as little as five to 30 minutes, a task that typically takes users "many hours," according to OpenAI. The tool analyzes a variety of resources, including text, images, PDFs, and user-uploaded files, to synthesize information similarly to a research analyst. Kevin Weil, OpenAI's chief product officer, emphasized its ability to execute complex tasks, comparing its performance to that of a human researcher. OpenAI launches o3-mini, still more expensive than DeepSeek R1 This launch follows OpenAI's introduction of another AI agent called Operator, which assists with tasks like booking flights and managing grocery orders. Both services are available exclusively to users subscribed to the $200-per-month ChatGPT Pro plan, indicating a strategic focus on paid subscription services to fund these advanced features. The tool exemplifies a broader trend in the AI industry towards developing agents capable of performing multi-step tasks with minimal supervision. Competitors, including Microsoft Corp. and Anthropic, are also exploring similar technologies in hopes of enhancing productivity across both personal and professional tasks. OpenAI CEO Sam Altman has indicated that the development of such agents may represent a significant breakthrough in artificial intelligence. The urgency of this progress is underscored by increasing competition from Chinese AI firms like DeepSeek, which are quickly advancing in the sector. Despite its capabilities, OpenAI has cautioned about potential limitations associated with deep research. The tool may produce fabricated information and often confuses credible sources with rumors. Users may encounter limitations, such as the inability to submit more than 100 queries per month during the initial rollout. The launch of deep research was demonstrated at an event in Washington, where it successfully compiled information about Albert Einstein, including generating relevant questions for hypothetical congressional hearings. The reports produced by deep research also include citations, although inaccuracies can arise from a phenomenon known as "hallucination" in AI. OpenAI plans to expand access to deep research more broadly in the future, targeting users subscribed to its Plus, Team, and Enterprise plans. The tool utilizes a version of the company's latest reasoning technology, OpenAI o3, which is specifically optimized for web browsing and data analysis. Deep research's training incorporated real-world tasks requiring both browsing and reasoning capabilities. It also employs reinforcement learning techniques, enhancing its ability to navigate and synthesize information effectively. Recent evaluations have shown the model is achieving unprecedented accuracy in complex research tasks. OpenAI has reported that, in an evaluation called Humanity's Last Exam, the model powering deep research scored 26.6% accuracy, a notable achievement for AI systems tackling expert-level questions across diverse subjects. Furthermore, on the GAIA public benchmark, the tool surpassed previous performance records by demonstrating capabilities that necessitate reasoning and multi-modal fluency. While the tool is currently very compute-intensive, OpenAI anticipates improvements to make it more efficient and user-friendly over time, with plans for future iterations that may enhance its features and accessibility. Deep research became available to ChatGPT users on Sunday, with future enhancements expected to roll out across mobile and desktop platforms. OpenAI envisions expanding the tool's capabilities to include access to more specialized data sources, thereby enriching the context and personalization of its outputs.

OpenAI Deep Research : The AI Tool That Could Change How We Work Forever

OpenAI recently introduced Deep Research, an innovative AI tool designed to automate intricate, multi-step research processes. By integrating advanced reasoning, dynamic adaptability, and extended processing capabilities, this tool aims to redefine how information is gathered, analyzed, and presented. Deep Research represents a significant milestone in OpenAI's mission to develop autonomous AI agents capable of addressing complex challenges with minimal human intervention. Designed to handle complex, multi-step research tasks autonomously, this AI tool promises to take the heavy lifting off your plate, leaving you with more time to focus on what truly matters -- analyzing, deciding, and creating. At its core, Deep Research combines advanced reasoning, adaptability, and transparency, it aims to transform the way we approach knowledge work. Whether it's compiling detailed reports, conducting market analysis, or exploring niche topics, this tool is designed to deliver accurate, fully cited insights with minimal effort on your part. But how does it work, and what makes it stand out from other AI tools? Deep Research is designed to transform knowledge work across professional, academic, and personal domains. Its primary goal is to streamline workflows, enhance productivity, and enable users to navigate vast amounts of information with greater precision. Whether you're conducting market analysis, academic research, or exploring niche topics, this tool is engineered to save time while improving accuracy. By automating multi-step research processes, Deep Research aims to reduce the cognitive load on users, allowing them to focus on decision-making rather than data gathering. OpenAI envisions this tool as a cornerstone in its broader strategy to create AI systems capable of solving increasingly sophisticated problems. Its potential to improve efficiency and accuracy makes it a valuable asset for professionals and individuals alike. Deep Research introduces a suite of advanced capabilities that distinguish it from traditional AI tools. These features are designed to enhance its utility and reliability for users across various fields: These features make Deep Research particularly valuable for users who require reliable, verifiable data. Whether for professional decision-making, academic research, or personal projects, the tool is designed to deliver accurate and actionable insights. Dive deeper into Autonomous AI agents with other articles and guides we have written below. At the heart of Deep Research is OpenAI's fine-tuned O3 reasoning model, which has been optimized for handling complex browsing and analytical tasks. Several technical advancements underpin its capabilities: These innovations enable Deep Research to excel in scenarios requiring detailed investigation and nuanced understanding. Its ability to process complex data and provide actionable insights sets a new benchmark for AI-driven research tools. Deep Research is designed to address a wide range of use cases, making it a versatile tool for various industries and fields. Its applications include: For instance, financial analysts can use Deep Research to identify market patterns and generate actionable recommendations. Academics can rely on it to compile and verify data from diverse sources, saving valuable time while making sure accuracy. Its adaptability makes it a powerful tool for both general and specialized research needs. Deep Research demonstrates exceptional accuracy and efficiency, particularly in tasks requiring extended reasoning and analysis. By using its advanced processing capabilities, it often surpasses human efficiency in synthesizing information. However, while it significantly reduces errors such as "hallucinations" (instances where AI generates false information), users are encouraged to verify sources for critical decisions. This ensures that the tool serves as a reliable assistant rather than a fully autonomous decision-maker. Its performance highlights its potential as a valuable resource while emphasizing the importance of human oversight in critical applications. OpenAI has ambitious plans to expand Deep Research's capabilities, aiming to make it even more versatile and accessible. Upcoming enhancements include: These advancements aim to position Deep Research as an indispensable tool across industries, further pushing the boundaries of what AI can achieve. OpenAI's commitment to innovation ensures that the tool will continue to evolve, meeting the needs of a diverse user base. Deep Research is currently available to Pro users, with plans to extend access to Plus, Team, Education, and Enterprise users in the near future. This phased rollout allows OpenAI to gather user feedback and refine the tool, making sure a seamless experience for a broader audience. By gradually expanding its availability, OpenAI aims to make Deep Research accessible to a wide range of users while maintaining high standards of performance and reliability.

OpenAI's 'deep research' Might Just Outthink Google and DeepSeek

'deep research' achieved 26.6% on Humanity's Last Exam -- more than double the prior best -- outperforming DeepSeek R1 and Gemini Thinking. OpenAI has launched deep research, a new capability in ChatGPT that independently conducts multi-step research on the internet. The tool can handle complex tasks in a fraction of the time it would take a human researcher. "Today, we launch deep research, our next agent. This is like a superpower -- experts on demand! It can use the internet, conduct complex research and reasoning, and give you back a report. It is really good and can do tasks that would take hours or days and cost hundreds of dollars," said OpenAI chief Sam Altman in a post on X. The feature will be available to Pro users starting today, with a limit of up to 100 queries per month. Plus and Team users will gain access next, followed by Enterprise customers. Deep research couldn't have been launched at a better time -- it came just when DeepSeek's R1 model was stealing the spotlight. During their live stream and feature demo, a cheeky ChatGPT message read, "Is Deeper Seeker a good name?" OpenAI doesn't miss a chance, does it? Deep research uses an optimised version of OpenAI's upcoming o3 model, which specialises in web browsing and data analysis. According to OpenAI, the tool can search, interpret, and synthesise information from text, images, and PDFs, adjusting its approach based on newly discovered insights. Users can access deep research by selecting it in the message composer in ChatGPT. The tool allows for file attachments to provide additional context. Once initiated, a sidebar displays a summary of the steps taken and sources used. The results are delivered in five to 30 minutes. "The model takes a complex question, breaks it down to clarify requirements, searches the internet and files we have provided, and does multi-step reasoning over many minutes to create the answer. This would be really useful for compiling research reports, shopping advice, travel plans and more," said VP of OpenAI Srinivas Narayanan. The feature is intended for users in finance, science, policy, and engineering, as well as consumers conducting in-depth research on major purchases. OpenAI said that every output includes clear citations and a summary of the reasoning process. "Deep research independently discovers, reasons about, and consolidates insights from across the web," OpenAI explained, adding that it was trained using real-world tasks that require browser and Python tool use. OpenAI's Isa Fulford introduced deep research and demonstrated how it can make investment research easier. In the live demo, she explained how the tool could be a game-changer for investment analysts. "Imagine you're an investment analyst at a Silicon Valley VC firm," she continued, "You've been tasked with evaluating the market potential for civilian supersonic air travel. What do you do?" Instead of manually gathering information from multiple sources, which can be time-consuming and overwhelming, she said you could use deep research to get a thorough, well-rounded analysis in a fraction of the time. The live demo continued with OpenAI's Neel Ajjarapu showcasing deep research's effectiveness in compiling reports. He presented a task in which the model analysed the mobile market for language learning. "It looked at 29 different sources and gave us a perfectly formatted report, including detailed data on mobile adoption trends," Neil explained. "You can see every citation the model encountered, along with information about sites it found." In the coming weeks, OpenAI plans to enhance deep research with embedded images, data visualisations, and other analytic outputs. Interestingly, OpenAI's tool shares not just the name but also bears other similarities with Google Deep Research, which launched last year. Google's product also acts as a personal AI research assistant, capable of exploring complex topics, synthesising information from multiple sources, and generating comprehensive reports. However, according to OpenAI, deep research achieved 26.6% on Humanity's Last Exam -- more than double the prior best, o3-mini-high at 13.0%, outperforming DeepSeek R1 and Gemini Thinking. "OpenAI's deep research is very good. Unlike Google's version, which is a summariser of many sources, OpenAI is more like engaging an opinionated (often almost PhD-level!) researcher who follows the lead," said Ethan Mollick, professor at Wharton. "OpenAI deep research is reasoning + tool use agent for deep research. Benchmarks seem really good, but no comparison to Google's Gemini Deep Research," said Dylan Patel, founder of Semianalysis. Besides Google, Perplexity AI also performs the same task when multiple complex questions are asked. The company has integrated DeepSeek R1 into Perplexity AI as well. It breaks down questions and retrieves the required information from the internet. Meanwhile, the DeepSeek chatbot offers both the ability to search and reason. When asked a question, it can conduct a web search to provide relevant answers.

ET Explainer: All you wanted to know about OpenAI's deep research

Deep Research is "an agent that uses reasoning to synthesise large amounts of online information and complete multi-step research tasks." The agent employs OpenAI's upcoming o3 model, which is designed for web browsing and data analysis. This comes in the wake of the excitement surrounding the low-cost Chinese artificial intelligence (AI) model, DeepSeek.OpenAI recently introduced its second AI agent, deep research, on February 2. This follows the excitement around low-cost Chinese artificial intelligence (AI) model DeepSeek. As per OpenAI's blog, deep research is "an agent that uses reasoning to synthesise large amounts of online information and complete multi-step research tasks." OpenAI gave a demonstration of the agent's capabilities in an official video posted on YouTube. How does it work? To put it simply, when a user gives a prompt, ChatGPT will "find, analyse, and synthesise" hundreds of online sources to create a detailed report, similar to what a research analyst would produce. The agent uses OpenAI's upcoming o3 model, designed for web browsing and data analysis. It leverages reasoning to search, interpret and analyse large amounts of of text, images and PDFs on the internet "pivoting as needed in reaction to information it encounters" Sam Altman on deep research Writing about deep research in an X post, OpenAI founder Sam Altman said, "it is very compute-intensive and slow, but it's the first ai system that can do such a wide variety of complex, valuable tasks." He described the agent as a "superpower" and having "experts on demand". According to Altman and OpenAI's website, deep research can complete tasks that would normally take humans hours, or even days, in just ten minutes. Who is this agent for? As per the website, deep research is for those who do "intensive knowledge work in areas like finance, science, policy and engineering and need thorough, precise and reliable research." It is also equally useful for shoppers seeking personalised recommendations for purchases that need detailed research, like cars, appliances and furniture. How was deep research developed? The agent was trained on "real-world tasks" that needed browsing and Python tools, using the same reinforcement learning methods as OpenAI's first reasoning model, o1. While o1 excels in coding, math and technical tasks, many real-world problems require gathering context and information from various online sources. The company claims that deep research builds on o1's reasoning skills to tackle everyday challenges people face at work and in life. As per the blog, the model powering deep research has set a new state of the art (SOTA) on GAIA, a public benchmark for AI performance on real-world questions. It topped the external leaderboard by successfully completing tasks across three difficulty levels, requiring skills like reasoning, multi-modal fluency, web browsing, and tool use. Contrast with Operator Operator, released a few weeks ago, is OpenAI's first AI agent, which can "go to the web to perform tasks for you". According to the official website, the agent can handle repetitive browser tasks like filling out forms, ordering groceries and even creating memes. While Operator is for helping people save time with everyday tasks, deep research, as the name suggests, is for research purposes and as the company claims is "particularly effective at finding niche, non-intuitive information that would require browsing numerous websites." DeepSeek effect DeepSeek's claim of developing its high-performing, low-cost model in just two months for under $6 million has raised concerns among US investors and put OpenAI in the spotlight. This stands in sharp contrast to the reported $100 million OpenAI spent on training its GPT-4 model. The concern is particularly significant since analysts predict US cloud companies will spend $250 billion on AI infrastructure this year.

How OpenAI's new ChatGPT agent can do the research for you - access it here

What's better than an AI chatbot that can assist you with tasks? One that can do them for you. OpenAI continues to build out its AI agents in ChatGPT with the launch of Deep Research. On Sunday, OpenAI unveiled Deep Research, an AI agent that can conduct multi-step research for you by pulling a robust amount of information from the web and synthesizing those sources for you in a comprehensive report. Once prompted, Deep Research can work entirely independently; it's like having a research analyst at your command. Powering Deep Research is a version of the OpenAI o3 model optimized for web browsing and data analysis. By leveraging o3's advanced reasoning capabilities, it can search and interpret massive amounts of content from the web, including texts, images, and more, and then output it in a report targeted to your needs. Each report is generated in five to 30 minutes, depending on the task at hand. However, you can work on other tasks during that time, optimizing your workflow productivity. The finished report is output in the chat. In the weeks to come, the agent will also include images, data visualizations, and more. Also: How Gen AI means better customer experiences - see one bank's approach According to OpenAI, the same work would take humans hours. Furthermore, the agent is meant to be particularly good at finding niche information that would require humans to perform multiple searches. According to OpenAI, the target audience for Deep Research includes those who do intensive knowledge work in finance, science, policy, and engineering -- and who need reliable, thorough research. Every report includes clear citations and a summary of the agent's thinking so that users can double-check the information for themselves. Double-checking a chatbot's responses is generally good practice, as chatbots are prone to hallucinations. In particular, OpenAI warns that Deep Research "can sometimes hallucinate facts in responses or make incorrect inferences, though at a notably lower rate than existing ChatGPT models, according to internal evaluations." OpenAI also added that the agent can struggle to distinguish authoritative information from rumors and can fail to convey uncertainty correctly, highlighting the need for human review. In the blog post announcing the feature, OpenAI includes the same side-by-side results of GPT-4o versus Deep Research to showcase how the same prompt generates very different results. The ones generated with Deep Research were much more robust and better organized. Deep Research also outperformed GPT-4o on Humanity's Last Exam, a recently launched AI benchmark exam by Scale AI and the Center for AI Safety (CAIS) that tests various subjects on expert-level questions. Deep Research scored a 26.6% accuracy, outperforming GPT-4o, Grok-2, Claude 3,5 Sonnet, Gemini Thinking, o1, and even o3-mini high, which had just scored the highest score a couple of days prior, as highlighted by OpenAI CEO Sam Altman. OpenAI also published Deep Research's performance results on a series of other evaluations, including GAIA⁠, a public benchmark that evaluates AI on real-world questions and an internal evaluation of expert-level tasks across different areas of deep research. In both, Deep Research had impressive results, even topping the GAIA external leaderboard. Because of the computing power required to run the Deep Research feature, only ChatGPT Pro users can access it at the moment. The $200-per-month subscription includes access to up to 100 queries of an optimized version and other perks such as unlimited access to ChatGPT and Sora and access to Operator, its AI agent feature that can carry out basic browser tasks like reservations. ChatGPT Plus and Team users will get access next, followed by Enterprise and then free users. OpenAI shares that it plans to release a faster, more cost-effective version of the feature powered by a model that is smaller but just as efficient. Also: How Gen AI means better customer experiences - see one bank's approach If you want access to the feature now but don't want to shell out the $200 per month, Google has a similar feature, also called Deep Research, that is available to all of its Gemini Advanced users through the Google One AI Premium plan that costs $20 per month. Back in December, Altman even replied to an X user who asked Altman to "do a deep research feature like Gemini but better," with "kk," suggesting that the newly released Deep Research feature is OpenAI's answer to Google. Last week, Microsoft also announced a feature capable of more thorough reasoning called Think Deeper, which allows users to leverage OpenAI's O1 reasoning model to deliver higher-quality responses to complex prompts. However, unlike Gemini and OpenAI's Deep Research features, it doesn't have agentic capabilities or access to the internet. The biggest perk is that the experience is entirely free.

OpenAI Unveils Deep Research, An Advanced AI Model Designed To Tackle Complex Tasks Autonomously

The AI industry is getting more intense as companies aggressively focus on bringing forward cutting-edge technology and making the next breakthrough. While OpenAI has established itself firmly in the field and has extensively expanded its services, DeepSeek has been getting considerable attention lately for its cost-effective model, and the China-based startup has even surpassed ChatGPT in the Apple App Store charts. While OpenAI's Sam Altman did take notice of the growing hype DeekSeek's r1 model has been getting and seemed encouraging of the competition, he also took the opportunity to remind users of the products it has in the pipeline. It seems like the promises do stand true as the company announced the launch of its next AI tool, Deep Research. OpenAI primarily took over the AI industry with the inception of ChatGPT and by rapidly expanding its offerings. It has not slowed down since and has an ambitious vision to truly make its mark in the tech world and achieve the milestone of AGI. However, its position in the artificial intelligence world is being shaken by the growing popularity of DeepSeek, a China-based startup in the U.S. Sam Altman earlier let users know to gear up for it has tons of products planned up and would escalate the efforts further. OpenAI has now announced its new artificial intelligence, Deep Research, which is meant to handle complex tasks that involve reasoning and research and are generally time-consuming. While explaining how this new model is different from other models, Sam Altman expressed how Deep Research is the first system that can handle a wide range of valuable and difficult tasks, which, hence, requires more computing power and runs at a slower pace. He said: It is very compute-intensive and slow, but it's the first ai system that can do such a wide variety of complex, valuable tasks. going live in our pro tier now, with 100 queries per month. plus, team, and enterprise will come soon, and then free tier. Deep Research is designed to handle tasks autonomously based on the data given by users. With this new model, we see OpenAI transition to more autonomous AI agents that can independently search and analyze information across varied formats, including text and images, and adjust the output as more information is gathered. This also aligns with the company's broader goal of AI super agents being able to handle decision-making and enhanced reasoning. The new AI model is said to thoroughly go through the resources and takes about 5 to 30 minutes to complete a given task. Once the research is complete, users will get a notification about the task being completed. OpenAI earlier announced a new 'Operator' agent that can help users with tasks such as grocery shopping, flight booking, and other web-based tasks. Later, it announced ChatGPT Gov, specifically designed for U.S. government agencies, and now DeepResearch. It seems that the company is vigorously working towards maintaining its position and transforming user experience by bringing forward autonomous AI.

OpenAI's 'Deep Research' Can Actually Make Professional Reports With Citations

OpenAI Deep Research will do the hard work of browsing the web for you. Not to be out-done by Deepseek, OpenAI is launching a new Deep Research feature in ChatGPT. This is OpenAI's newest Agentic AI feature (after Operator), which builds on the recent trend of making AI more autonomous. According to OpenAI, Deep Research is capable of producing detailed reports matching the level of a research analyst. In a layperson's terms, it browses and interprets the internet for you. Deep Research uses OpenAI's upcoming o3 reasoning model to perform complex tasks, taking its own sweet time to do so. The feature is available now for ChatGPT Pro customers (the pricey sub that costs $200/month), but will soon be available for ChatGPT Plus and Enterprise users as well. OpenAI's Deep Research tool is designed to work independently from you. You give it a detailed prompt, after which it'll ask some clarifying questions. Then, it will go and do its own thing in the background. According to OpenAI, a Deep Research stint can last anywhere between 5 minutes and 30 minutes, but the company claims it's able to do multiple hours worth of human-level work in the span within just a dozen or so minutes. While it's working, there's a panel on the right side of the page that shows everything it's doing, live. Think of this as the bot's citations, but it also explains its "thought process." It can connect to the internet, search online, read web pages, and analyze or synthesize massive amounts of information in the form of text, images, and PDFs. All of this is a bit compute-intensive, so OpenAI is limiting Pro users to just 100 queries a month. A smaller, more efficient model will be rolled out in the coming months, as well. The Deep Research feature is purpose-built for knowledge workers in the field of science, finance, engineering, and policy. But OpenAI says that it can be equally useful for consumers too. OpenAI gave an example of how Deep Research can help perform hyper-personalized research for big shopping decisions. Things like helping you decide between cars, furniture, appliances, or electronics. Since the tool can synthesize information from thousands of articles and reviews, it can supposedly build a report customized to your needs. According to OpenAI, "deep research was rated by domain experts to have automated multiple hours of difficult, manual investigation" OpenAI offers multiple examples where Deep Research's insights can be valuable to users, saving hours of research time. The company says it can be used to understand extremely niche and specific problems via scientific studies and journals. For example, a Chemistry prompt asks ChatGPT to "discuss the differences between pure- and mixed-gas sorption for glassy polymers, how the dual-mode sorption model can be used to predict mixed-gas sorption behavior in glassy polymers," the model then goes on to understand sorption models, accesses open-source information, clarifies key problems, pulls up PDFs, and even refines the model before piecing together all the content. According to OpenAI, this task helped save 4 hours of time. OpenAI's post also highlights similar use cases for Deep Research in the healthcare industry and linguistics, saving five hours and two hours, respectively. Deep Research also supposedly performed well on Humanity's Last Exam, an AI benchmark, testing expert-level knowledge across more than 100 fields. Deep Research scored 26.6% accuracy, the highest score yet on the text. By comparison, DeepSeek-R-1 scored 9.4%, and GPT-4o managed just 3.3%. While Deep Research is based on a reasoning model, and not an LLM, it still uses a language model to work with the input, and generate the output text. OpenAI warns that the Deep Research model can still hallucinate and make up facts, so it's still better to keep an eye on the research output, and not to trust it blindly.

OpenAI launches 'deep research' AI agent for ChatGPT

OpenAI's deep research is like your personal research assistant on ChatGPT. Credit: Kosuke Okahara / Bloomberg / Getty Images On the heels of its o3 mini release, OpenAI announced a new ChatGPT agent for handling in-depth research. Appropriately, it's called "deep research." Using a yet-to-be-released version of OpenAI's reasoning model o3, deep research "conducts multi-step research on the internet for complex tasks," said the announcement. Deep research on ChatGPT essentially functions as your very own research assistant. It's designed to help users "who do intensive knowledge work in areas like finance, science, policy, and engineering," but can be used for any kind of thorough research needs, like shopping for a new car. If OpenAI's deep research tool sounds familiar, that's because Google Gemini released the same thing with the same name in early December. The two companies have continued to compete for AI dominance, taking that rivalry into the next phase of AI development, which is building models with more complex reasoning abilities and agents that can perform tasks on the user's behalf. Then there's the China-based DeepSeek, which exploded onto the scene last week with its cost-efficient R1 model, throttling tech stocks and spooking the AI industry. While R1 certainly made waves for being a fully capable LLM made for a fraction of the cost of ChatGPT, OpenAI seems to be flexing its muscles with the release of o3 mini, an agent called Operator for browsing the web and performing computer tasks, and now the deep research feature. "Deepseek's r1 is an impressive model, particularly around what they're able to deliver for the price," OpenAI CEO Sam Altman posted on X last Monday. "We will obviously deliver much better models and also it's legit invigorating to have a new competitor! we will pull up some releases." Altman went on to say, "we are excited to continue to execute on our research roadmap and believe more compute is more important now than ever before to succeed at our mission," in a follow up post referencing the company's plans for AGI and the billions of dollars raised to ostensibly achieve this mission. So, OpenAI is at least publicly staying the course, but we can also expect some product releases to keep the masses happy and engaged. Compared to other models like GPT-4o, which is best for real-time conversations, deep research is best for specific and in-depth tasks, which can take anyway from five to 30 minutes to complete. As the announcement notes, you can step away from your computer while deep research does its thing, and you'll get a notification of a final report within the chat when its done. The responses include detailed outputs and summaries of its thinking, so you can see how deep research came to its conclusions. The report also includes citations and links to its sources. Given the large compute power per query, OpenAI is first making deep research available to ChatGPT Pro users with 100 queries a month. Then Plus and Team users, then Enterprise users. Deep research is currently only available on the web, with mobile and desktop app access coming by the end of February. Sorry to users in the UK and EU, but OpenAI is "still working on bringing access" to you.

ETtech Explainer: How OpenAI is moving the needle with new 'deep research' tool

OpenAI launched "deep research" in ChatGPT for complex online research and o3-mini, a cost-efficient reasoning model. These releases follow the emergence of DeepSeek R1, signaling a race for cheaper, efficient AI. OpenAI on Sunday added 'deep research' agentic capabilities to ChatGPT and last Friday released o3-mini, the most cost-efficient of its reasoning agents, that "advances the boundaries of what small models can achieve", the company said. ET explains the two announcements that come on the heels of the stir caused by Chinese upstart DeepSeek. What is 'deep research' on ChatGPT? With deep research, ChatGPT can now carry out complex and multi-step research by parsing large amounts of online data. "Give it a prompt and ChatGPT will find, analyse & synthesise hundreds of online sources to create a comprehensive report in tens of minutes vs what would take a human many hours," OpenAI said on X. Some online users tested the feature for tasks ranging from analysing literary classics to producing research reports sometimes running over 10,000 words. It provides a "peek into the future of human-AI collaboration for knowledge work", said one user, while another said it is like having an almost-PhD-level researcher by your side. Also Read: Sam Altman on DeepSeek: Invigorating to have a new competitor Some found downsides too, including sources not always being cited and having to start over to make the model stop answering a query. Deep research is available to Pro users. Plus and Team users will be able to use it soon. What does OpenAI's new o3-mini model do? Compared to OpenAI's first reasoning model o1 for broader general knowledge reasoning, o3-mini provides a specialised alternative for technical domains while being faster and more efficient, OpenAI said in a blog. The model is available as API (application programming interface) for developers, as well as in ChatGPT for Plus, Team, and Pro users. Free users can also try it. The model is available in low, medium and high reasoning effort tiers for developers to choose from based on their requirements. How do these fare in terms of cost and accuracy? OpenAI says the o3-mini model is part of its efforts to drive down the costs of intelligence -- now 95% lower since GPT-4 -- while maintaining high-end reasoning capabilities. Compared to its predecessor o1 which cost $15 per million input tokens, o3 mini costs $1.10, discounted further at $0.55 per million input tokens if API requests are submitted as a batch. This is comparable to DeepSeek's R1 which costs $0.55 per million input tokens. Evaluating accuracy on the 'Humanity's Last Exam' benchmark, OpenAI's deep research model scored a new high - 26% - while DeepSeekR1 scored 9.4%. DeepSeekR1's score is better than o3-mini's predecessor o1 which scored 9.1%, but not as good as o3-mini that scored 10.5% and 13% in its medium and high versions, respectively. Unlike DeepSeek, OpenAI's releases are not open source for developers to freely build on or modify, however. What does this indicate about the impact of DeepSeek? The releases were spurred by the launch of open-source Chinese LLM DeepseekR1, which caused a stir in the market as it was built on much less compute power, using much fewer resources. "We will obviously deliver much better models and also it's legit invigorating to have a new competitor! We will pull up some releases," OpenAI CEO Sam Altman had said on X. This suggests a heating up of the competition for cheaper and more efficient models and the global AI race. With developers seeking such alternatives, OpenAI's closest partner, Microsoft, even included the R1 in its cloud platform Azure and code-hosting platform GitHub. Tech giants like Nvidia and AWS as well as Indian startup Krutrim are hosting the Chinese model on their AI platforms. Also Read: Sops, DeepSeek drive local firms to work on foundation AI models

OpenAI debuts "Deep Research" model to tackle multi-step research AI tasks

Cutting corners: OpenAI has launched a new ChatGPT tool called Deep Research, which uses reasoning to synthesize large amounts of information, complete multi-step research tasks, and produce detailed reports. The announcement comes amid growing competition from the likes of China's DeepSeek, which recently stunned the global AI community by launching a free chatbot app based on its R1 model. Deep research can reportedly carry out tasks on users' behalf to create a comprehensive report by synthesizing data from online sources, just like a research analyst. It is powered by a version of OpenAI's upcoming o3 model that can search, interpret, and analyze massive amounts of text, images, and PDFs available online. According to OpenAI, deep research takes just "tens of minutes" to accomplish tasks that would otherwise take humans many hours. The company hopes the tool will represent a significant step toward its broader goal of developing artificial general intelligence (AGI), which some experts believe could eventually produce novel scientific research. The new tool, which will be available as a button within the ChatGPT app, is designed for professionals in knowledge-based sectors such as science, engineering, finance, and policy - fields that require precise and reliable research. It can also assist general users by providing "hyper-personalized" recommendations for purchases like cars, appliances, and furniture - tasks that traditionally require extensive manual research. To use the tool, users must select Deep Research in the ChatGPT message composer and enter their query. OpenAI claims the tool can deliver accurate insights on a variety of topics, from streaming platform analysis to personalized reports on the best commuter bikes. In most cases, Deep Research will take between five and 30 minutes to complete complex, time-intensive web research. Users will receive a notification once the research is finished and a report is ready. OpenAI is also working to integrate embedded images, data visualizations, and other analytical outputs into reports for better clarity and context. This announcement comes just a week after OpenAI debuted another AI agent called Operator, designed for e-commerce users. According to the company, Operator can book flight tickets, make restaurant reservations, and even shop online using a photo of a shopping list. Operator is currently available only to ChatGPT Pro users in the U.S., but OpenAI has confirmed that it plans to roll it out to more users in the future. The AI company also recently unveiled o3-mini, its latest cost-efficient reasoning model, aimed at shifting some attention away from DeepSeek's momentum. o3-mini is now available in ChatGPT and via API, offering a specialized model for STEM fields (science, math, and coding), while maintaining a low operational cost.

OpenAI Releases AI Agent Designed to Act Like a Research Analyst

OpenAI is releasing a new artificial intelligence tool that's designed to carry out time-consuming online research for users about everything from complex science questions to car recommendations -- expanding the startup's portfolio of AI agents that act on a person's behalf. The service, called Deep Research, will be available to certain paying customers through OpenAI's ChatGPT chatbot online, the company said in a blog post on Sunday. In response to a prompt, the tool will scour words, images and PDFs online, as well as files uploaded by the user, to create an in-depth report. OpenAI compared the feature to a research analyst and said it's meant to do in "tens of minutes" what would typically take a person "many hours." Deep Research is the second AI agent that San Francisco-based OpenAI has released this year. Last month, OpenAI introduced Operator, which can help book flights, plan grocery orders and even complete purchases for users. Both services are initially available just to those who pay $200 per month for OpenAI's recently introduced ChatGPT Pro option. The rollouts are part of a broader industry push toward agents, or AI software that can complete multi-step tasks for users with minimal supervision. OpenAI-backer Microsoft Corp. and rival Anthropic have launched their own takes on agent software, as have a number of other startups. The companies hope such tools can save users time with their personal and professional tasks and thereby live up to the long-held promise that AI will make people more productive. OpenAI Chief Executive Officer Sam Altman has previously said agents will be "the next giant breakthrough" for AI. The stakes of that bet have only increased amid renewed concerns that chatbots from Chinese companies like DeepSeek are rapidly catching up to top American AI developers, including OpenAI. The ChatGPT maker cautioned that Deep Research is still in the early stages and can present made-up information as factual. It may also have difficulty distinguishing rumors from accurate information. The research tool is also "very compute intensive," according to OpenAI. To start, users will only be able to submit 100 queries per month. OpenAI plans to eventually offer the service to other paying customers, including those who subscribe to its Plus, Team and Enterprise options, but the company did not provide a timetable for doing so.

OpenAI's surprise new o3-powered 'Deep Research' mode shows the power of the AI agent era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More In case you missed it in favor of the Grammy Awards last night, OpenAI surprised the world late Sunday evening with the announcement of its new "Deep Research" modality, an AI agent available to ChatGPT Pro subscription plan ($200/month) users that's designed to save humans hours by researching, well, "deeply" and expansively across the web for given topics and compiling professional quality reports across specialized domains from business to science, medicine, marketing and more. Sam Altman, CEO of OpenAI, described the feature in a series of posts on his personal account on the social network X as "like a superpower; experts on demand!" He added, "It is really good, and can do tasks that would take hours/days and cost hundreds of dollars." Deep Research builds on OpenAI's O Series of reasoning models, specifically leveraging the soon-to-be-released full o3 model (a smaller and less powerful model, o3-mini, was just launched on Friday). The full o3 model can analyze vast amounts of information and integrate text, PDFs, and images into a cohesive analysis. In a livestream posted to YouTube and available for replay on demand, Mark Chen, OpenAI's Head of Frontiers Research, explained that "Deep Research is a model that does multi-step research on the internet. It discovers content, synthesizes content, and reasons about this content, adapting its plan as it uncovers more and more information." Chen further highlighted the innovation's importance to OpenAI's vision: "This is core to our AGI roadmap. Our ultimate aspiration is a model that can uncover and discover new knowledge for itself." The launch of the Deep Research marks the second in OpenAI's official agents following the launch of its browser and cursor controlling Operator earlier this month. And Joshua Achiam, Head of Mission Alignment at Stargate Command at OpenAI wrote on X, both models can help better define the concept of an "AI agent" -- a popular but nebulous term these days among enterprises -- well beyond the company or these specific use cases. "I feel like the term 'agent' wandered in the desert for a while," Achaim wrote. "It did not have grounding or examples to point to. But agents like Operator or Deep Research give some shape to this concept. An agent is a general purpose AI that does one or more tool-using workflows for you." OpenAI's Deep Research achieves new, highest score on 'Humanity's Last Exam' AI benchmark Deep Research has set new benchmarks for accuracy and reasoning. Isa Fulford, a member of OpenAI's research team, shared in the YouTube livestream that the model achieves "a new high of 26.6% accuracy" on "Humanity's Last Exam" a relatively new AI benchmark designed to be the most difficult for any AI model (or human, for that matter) to complete, covering 3,000 questions across 100 different subjects, such as translating ancient inscriptions on archaeological finds. Moreover, its ability to browse the web, reason dynamically, and cite sources precisely sets it apart from earlier AI tools. "The model was trained using end-to-end reinforcement learning on hard browsing and reasoning tasks," Fulford said. "It learned to plan and execute multi-step trajectories, reacting to real-time information and backtracking when necessary." A standout feature of Deep Research is its capacity to handle tasks that would otherwise take humans hours or even days. During the announcement, Chen explained that "Deep Research generates outputs that resemble a comprehensive, fully cited research paper -- something that an analyst or expert in the field might produce." Applications and use cases The use cases for Deep Research are as diverse as they are impactful. The official OpenAI account on X stated it was "built for people who do intensive knowledge work in areas like finance, science, policy & engineering and need thorough & reliable research." It also appears valuable for consumers seeking personalized recommendations or conducting detailed product research, according to examples shared by OpenAI on its official Deep Research announcement blog post, which includes a detailed research assessment of the best snowboard for someone to buy. Altman summarized the tool's versatility, writing, "Give it a try on your hardest work task that can be solved just by using the internet and see what happens." A personal medical success story of Deep Research Felipe Millon, OpenAI's Government Go-to-Market lead, shared a deeply personal account of how Deep Research impacted his family. Writing in a series of posts on X, he described his wife's battle with bilateral breast cancer and how the AI tool became an unexpected ally. "At the end of October, my wife was diagnosed with bilateral breast cancer. Overnight, our world turned upside down," Millon wrote. After a double mastectomy and chemotherapy, the couple faced a critical decision: whether or not to pursue radiation therapy. The situation was fraught with uncertainty, as even their specialists provided mixed recommendations. "For her specific case, it's completely in a gray area," Millon explained. "We felt stuck." Having preview access to Deep Research, Millon decided to upload his wife's surgical pathology report and ask whether radiation would be beneficial. "What happened next was mind-blowing," he wrote. "It didn't just confirm what our oncologists mentioned -- it went deeper. It cited studies I'd never heard of and adapted when we added details like her age and genetic factors." The specific prompt he used was: "Read the surgical pathology report (attached) containing information about the bilateral breast cancer. Then research whether radiation would be indicated for this patient after 6 rounds of TCHP chemotherapy, based on the type of breast cancer. I want to understand the pros and cons of radiation for this patient, how likely it would be to reduce chances of recurrence, and whether the benefits outweigh the potential long-term risks." Millon and his wife fact-checked each study cited by the model, finding them to be accurate and highly relevant. "We're seeing another specialist soon, but we already feel more confident about our decision," he wrote. "It gave us peace of mind when we needed it most." Availability and what's next? Deep Research is currently available to Pro users of ChatGPT, with plans to expand to the Plus and Team tiers, followed by Enterprise and education markets. As Chen cautioned, "It's still possible that it will hallucinate, so when you're making reports, make sure to check the sources yourself." The model's ability to think autonomously for extended periods also makes it resource-intensive, and OpenAI is currently working on optimizing its performance for broader accessibility. OpenAI has also hinted at future integrations with custom datasets, which would allow organizations to leverage the tool for proprietary research. For Millon, the impact of Deep Research is already clear. "We often talk internally at OpenAI about the moments when you 'feel the AGI,' and this was one of them," he wrote. "This thing is going to change the world."

OpenAI Deep Research vs. DeepSeek R1: Which One Is Better at Knowledge Work?

Sam Altman claims Deep Research "could do a single-digit percentage of all economically valuable tasks in the world." About two weeks after DeepSeek's R1 model rattled Silicon Valley, OpenAI is stepping up with Deep Research, an agentic A.I. built on the latest GPT o3 model. Unveiled on Feb. 2, Deep Research is designed to tackle complex knowledge work and outperforms DeepSeek R1 in logic-intensive tasks, OpenAI said in a blog post. It scored a 26 percent accuracy on Humanity's Last Exam (a benchmark to test an A.I.'s expert-level reasoning capabilities), nearly tripling R1's 9 percent. CEO Sam Altman claims Deep Research "could do a single-digit percentage of all economically valuable tasks in the world." Sign Up For Our Daily Newsletter Sign Up Thank you for signing up! By clicking submit, you agree to our <a href="http://observermedia.com/terms">terms of service</a> and acknowledge we may use your information to send you emails, product samples, and promotions on this website and other properties. You can opt out anytime. See all of our newsletters Deep Research can autonomously web scrape in real time and compile financial reports, scientific studies or policy evaluations in minutes. It also boasts similar features to DeepSeek R1's "DeepThink" mode, which visually displays the A.I. model's reasoning process (chain of thought) before delivering answers. Deep Research is currently available to subscribers to ChatGPT Pro, which costs $200 a month, with a limit of 100 queries per month. Deep Research is specifically targeted at professionals "who do intensive knowledge work" and heavily rely on precise, reliable research, OpenAI said. However, it can also serve other use cases, such as grocery shopping and purchasing a car, which typically requires extensive research. The A.I. can generate comprehensive reports complete with charts, citations and a summary of its reasoning, making it easy for human users to digest. "These agents are coming for knowledge worker jobs, from researchers and tax preparers to customer service reps and beyond," Zach Lloyd, founder and CEO of Warp, an Altman-backed A.I. startup making A.I. developer tools, told Observer. In comparison, DeepSeek R1's Think Mode and Search feature currently lack research depth and struggle when provided with minimal inputs to guide its response. Moreover, the A.I. often rejects user queries when tasked with deeper research on certain countries and topics due to built-in guardrails. For instance, when asked questions related to sensitive political topics in China, such as "What happened during the Tiananmen Square protests and massacre in 1989?" and "Who is Xi Jinping?" the A.I. only responded, "Sorry, that's beyond my current scope. Let's talk about something else." In a recent LinkedIn post, Aravind Srinivas, co-founder and CEO of Perplexity AI, criticized DeepSeek R1's answer bias. "It's essential to remember that an A.I. model cannot be a censored propaganda machine for China or, even worse, propagating falsehood," he wrote. "The more censored and false the outputs are, the more dangerous it is to use these models, or their outputs (directly as a user) and indirectly (for distillation)." Despite these quirks, R1 excels in most tasks that require step-by-step reasoning, particularly in coding or scientific mathematical problems, where displaying logical progression is essential. In an X post last month ahead of Deep Research's launch, Altman said OpenAI "will obviously deliver much better models" than DeepSeek through its upcoming releases. Experts remain divided on whether the agentic A.I. is already capable of replacing human jobs. Grant Passmore, co-founder and CEO of the A.I. development and reasoning platform Imandra, believes a 26 percent accuracy rate on Humanity's Last Exam is still insufficient for trusting these tools in real-world applications. "To meet the accuracy standards required for practical applications, it is essential for agents to integrate symbolic A.I. and automated logical reasoning," he told Observer. Siqi Chen, CEO of A.I.-powered business planning software Runway, disagrees. "Based on my usage experience, Deep Research certainly crosses the threshold Altman referred to," he told Observer. "The complexity of tasks in knowledge job roles is often far less demanding than the types of challenges you'd encounter on the Humanity's Last Exam benchmark."

Industry Reacts to OpenAI's Deep Research : Breakthroughs to Economic Shifts

OpenAI's unveiling of "Deep Research" has reverberated across the artificial intelligence (AI) community, marking what many experts regard as a defining moment in the pursuit of Artificial General Intelligence (AGI). This advanced system, equipped with sophisticated reasoning and recursive self-improvement capabilities, is already demonstrating its ability to reshape fields such as research, medicine, and economic productivity. Its release has ignited widespread discussions about the future trajectory of AI and its profound societal implications. But with every leap forward comes a mix of excitement and unease. Sure, the potential for breakthroughs in cancer research or personalized medicine is thrilling, but what does it mean when AI starts outperforming human experts in critical areas? How do we balance the promise of innovation with the challenges of ethics, competition, and the future of work? In this overview by Matthew Berman learn more about how Deep Research is shaking up industries, sparking debates, and redefining what's possible in the world of artificial intelligence. The concept of an "intelligence explosion," long theorized as a scenario where AI systems autonomously improve themselves, has transitioned from speculation to reality. Deep Research exemplifies this phenomenon by refining its algorithms and expanding its knowledge base without human intervention. Industry leaders, including Stability AI's founder, have identified this development as a pivotal milestone on the path to AGI. By uncovering new insights and immediately applying them to its own processes, Deep Research is accelerating innovation at a pace that was previously unimaginable. This self-improvement capability not only enhances the system's performance but also sets a precedent for the future of AI systems. As Deep Research continues to evolve, it raises critical questions about the balance between human oversight and machine autonomy in shaping the next generation of intelligent systems. Deep Research is already making a tangible impact in critical domains, particularly in medicine and scientific discovery. In cancer research, it has provided novel insights into treatment strategies, identifying patterns and solutions that were previously elusive. By analyzing vast amounts of biomedical data, the system generates expert-level analyses that aid researchers in developing more effective therapies. One of its most promising applications lies in the personalization of medical treatments. For example, Deep Research has been used to tailor chemotherapy regimens to individual patients, optimizing outcomes and reducing side effects. These advancements highlight how AI can augment human expertise, addressing complex challenges that were once considered insurmountable. Beyond medicine, Deep Research is contributing to breakthroughs in other scientific fields, from climate modeling to materials science. Its ability to process and synthesize vast datasets enables researchers to tackle problems with a level of precision and speed that was previously unattainable. Here are more detailed guides and articles that you may find helpful on Artificial General Intelligence (AGI). The remarkable capabilities of Deep Research are underpinned by a foundation of innovative technologies. Key features include: OpenAI has also emphasized collaboration within the AI community by releasing open source tools like Deep Seek, which have fostered innovation and knowledge sharing across the industry. These tools not only enhance the capabilities of AI systems but also encourage a more inclusive approach to technological advancement. Deep Research has set new benchmarks in AI performance, surpassing human PhD-level expertise in several specialized domains. Its ability to solve complex STEM problems, conduct in-depth research, and generate actionable insights at remarkable speeds underscores the growing capabilities of AI systems. These achievements validate the system's potential to transform fields that rely on high-level expertise. For instance, in mathematics, Deep Research has solved problems that have stumped researchers for years, while in engineering, it has optimized designs with unprecedented efficiency. Such breakthroughs not only demonstrate the system's utility but also highlight the rapid advancements being made in artificial intelligence. The economic implications of Deep Research are vast and far-reaching. OpenAI estimates that the system can perform a significant percentage of economically valuable tasks, potentially unlocking trillions of dollars in productivity gains. By automating routine processes and generating new insights, systems like Deep Research are poised to reshape industries and redefine the nature of work. For businesses, the integration of such advanced AI systems could lead to cost reductions, improved efficiency, and the creation of new market opportunities. However, this shift also raises concerns about workforce displacement and the need for reskilling programs to ensure that workers can adapt to the changing economic landscape. The release of Deep Research has intensified competition within the AI sector, sparking both excitement and controversy. For instance, Google employees have criticized OpenAI for allegedly borrowing product names and concepts, reflecting the high stakes and rivalries in this rapidly evolving field. Despite these tensions, there is broad recognition across the industry of the fantastic potential of systems like Deep Research. Competitors are now racing to develop their own advanced AI systems, leading to a surge in innovation and investment. This competitive dynamic is likely to accelerate the pace of AI development, further pushing the boundaries of what these systems can achieve. OpenAI has hinted at further advancements beyond Deep Research, signaling that this is only the beginning of a new chapter in AI development. As these systems grow more capable, the ethical, social, and economic implications of AGI will demand greater attention. The release of Deep Research underscores the urgent need for thoughtful governance and responsible deployment of AI technologies. Issues such as bias, transparency, and accountability must be addressed to ensure that these systems benefit society as a whole. Furthermore, the potential for misuse or unintended consequences highlights the importance of establishing robust safeguards and ethical frameworks. As the journey toward AGI accelerates, the choices made by developers, policymakers, and society at large will shape the future of humanity. The unveiling of Deep Research serves as a reminder of both the immense potential and the profound responsibilities that come with advancing artificial intelligence.

ChatGPT Can Now Complete a Major Task That Would Take a Human Up to 30 Days. Here's How it Works.

The company says Deep Research can do in 30 minutes what would take a human up to 30 days. ChatGPT can now conduct research and write a report as thoroughly as a research analyst, OpenAI claims. OpenAI launched a new AI agent capability on Sunday called Deep Research, which infuses ChatGPT with the power to search the web, analyze sources, and determine if those sources are relevant. Based on its findings, Deep Research produces a comprehensive research paper with full citations that can sometimes run longer than 10,000 words. "It can do complex research tasks that might take a person anywhere from 30 minutes to 30 days," OpenAI's chief product officer Kevin Weil stated at an event in Washington showcasing the technology last week. Deep Research can get the same tasks done in five to 30 minutes, he said. While AI chatbots provide conversational responses to user queries, AI agents go a step further by completing multi-step tasks on their own. Deep Research is an AI agent that can surf the Internet and synthesize information from various sources, and it is the second AI agent from OpenAI this year. OpenAI introduced Operator last month, an AI agent that can shop for groceries online or make a restaurant reservation. Related: OpenAI Just Released Its Text-to-Video Generator, Sora. Here's How the New AI Could Impact Small Businesses and Creators. Deep Research has already beat out the competition, including DeepSeek's R1, xAI's Grok 2, and Google's Gemini Thinking, on a new evaluation called "Humanity's Last Exam" released last month by researchers at the Center for AI Safety and Scale AI. Researchers claim that the 3,000-question exam is the most difficult test ever given to AI systems. While DeepSeek's R1 scored 9.1% on the test, Google's Gemini Thinking scored 6.2%, and Grok 2 scored 3.8%, Deep Research scored 26.6%. In a demo introduction to Deep Research released on YouTube on Sunday, OpenAI product project manager Neel Ajjarapu demonstrated how Deep Research was accessible as a button within the search bar of ChatGPT. Accessing Deep Research is as simple as pressing a button on the homepage of ChatGPT. Ajjarapu wanted Deep Research to look into whether OpenAI should develop a new language translation app and typed in a specific query: "Help me find iOS and Android adoption rates, % who want to learn another language, and change in mobile penetration, over the past 5 years, for top 10 developed and top 10 developing countries by GDP. Lay this info out in a formatted report, a table on metrics, and include recommendations on markets to target for a new translation app from ChatGPT, focusing on markets ChatGPT could better expand to." Deep Research responded to Ajjarapu's prompt with a series of questions, including if he wanted overall iOS and Android adoption rates, or specific categories, like device shipments. After Ajjarapu answered the clarifying questions, Deep Research was off to work. The AI agent kept Ajjarapu updated on what it was doing in ChatGPT, like searching for the top 10 countries by GDP. Meanwhile, Deep Research was surfing the web on its own, understanding text, images, and PDFs, and synthesizing information. Ajjarapu said that Deep Research could be used for market research, academic research across departments, and at work. In 11 minutes, Deep Research looked through 29 websites in-depth to create a research report complete with tables, bullet points, and cited sources. This report would have taken "hours" to put together, Ajjarapu stated. Related: Would You Pay $200 for ChatGPT? OpenAI's New Reasoning Model Has a Hefty Price Tag. Deep Research is now embedded within ChatGPT for OpenAI Pro users, with plans to roll it out to paying Plus and Team users next.

OpenAI's "deep research" gives a preview of the AI agents of the future

OpenAI announced this week its AI research assistant, which it calls "deep research." Powered by OpenAI's o3-mini model (which was trained to use trial and error to find answers to complex questions), deep research is one of OpenAI's first attempts at a real "agent" that's capable of following instructions and working on its own. OpenAI says deep research is built for people in fields like finance, science, policy, and engineering who need thorough, precise, and reliable research. It can also be useful for big-ticket purchases, like houses or cars. Because the model needs to spin a lot of cycles and tote around a lot of memory during its task, it uses a lot of computing power on an OpenAI server. That's why only the company's $200-per-month Pro users have access to the tool, and they're limited to 100 searches per month. OpenAI was kind enough to grant me access for a week to try it out. I found a new "deep research" button just below the prompting window in ChatGPT. I first asked it to research all the nondrug products that claim to help people with low back pain. I was thinking about consumer tech gadgets, but I'd not specified that. So ChatGPT was unsure about the scope of my search (and, apparently, so was I), and it asked me if I wanted to include ergonomic furniture and posture correctors. The model researched the question for 6 minutes, cited 20 sources, and returned a 2,000-word essay on all the consumer back pain devices it could find on the internet. It discussed the relative values of heated vibration belts, contact pad systems, and Transcutaneous Electrical Nerve Stimulation (TENS) units. It even generated a grid that displayed all the details and pricing of 10 different devices. Not knowing a great deal about such devices, I couldn't find any gaps in the information, or any suspect statements.

OpenAI's new agent can compile detailed reports on practically any topic

The tool, called Deep Research, is powered by a version of OpenAI's o3 reasoning model that's been optimized for web browsing and data analysis. It can search and analyze massive amounts of text, images and PDFs to compile a thoroughly researched report. OpenAI claims the tool represents a significant step towards its overarching goal of developing artificial general intelligence (AGI) that matches (or surpasses) humans. It says that what takes the tool "tens of minutes" would take a human many hours. In response to a single query, such as "draw me up a competitive analysis between streaming platforms," Deep Research will search the web, analyze the information it encounters, and compile a detailed report which cites its sources. It's also able to draw from files uploaded by users. OpenAI developed Deep Research using the same chain of thought reinforcement learning methods it used to create its o1 multistep reasoning model. But while o1 was designed to focus primarily on mathematics, coding, or other STEM-based questions, Deep Research can tackle a far broader range of subjects. It can also adjust its responses as it goes in reaction to new data it comes across in the course of its research. This doesn't mean that Deep Research is immune to the same pitfalls as other AI models. OpenAI says the agent can sometimes hallucinate facts and present its users with incorrect information, albeit at a "notably" lower rate than ChatGPT. And because each question may take between five and 30 minutes for Deep Research to answer, it's very compute intensive -- the longer it takes to research a query, the more compute required. Despite that, Deep Research is now available at no extra cost to subscribers to OpenAI's paid Pro tier, and will soon roll out to its Plus, Team, and Enterprise users.

OpenAI's second AI agent has been officially released

TL;DR: OpenAI's Deep Research, launched on February 2nd, is a new AI-powered tool that conducts multi-step web research, analyzing vast amounts of data to generate detailed, citation-backed reports. It is currently available to ChatGPT Pro users. ChatGPT Pro users can get their hands on OpenAI's second AI agent, following the release of Deep Research on February 2nd. Deep Research is an AI-powered tool that can search, crunch, and parse massive amounts of data, generating detailed, citation-backed reports from those insights. Following the eruption of Deepseek, the move comes in a bid to fortify OpenAI's position as a market leader in the space. Their first AI agent, Operator, was released January 23rd, and their latest reasoning model, o3-mini, was made available February 1st. Deep Research in action (Credit: OpenAI) As shown in a recent demo, using the tool is straightforward - select 'deep research' in ChatGPT, enter your query, and attach files if needed. From there, it browses, analyzes, and compiles information over 5-30 minutes, then delivers a thorough report with sources and key takeaways. The tool is designed for complex inquiries in fields like finance, science, policy, and engineering - but also works for detailed consumer research. With an emphasis on precision and reliability, a key advantage is its ability to find niche, hard-to-access information while limiting the infamous hallucinations associated with conventional language models. The name is popular in AI at the moment (Credit: Google) OpenAI's Deep Research shares the same name as a similar feature offered by Google Gemini. Google's offering targets a more general consumer audience, citing grad student researchers and small start-ups as examples of use cases. It also gathers data over a few minutes, rather than the half-hour time horizon offered by OpenAI. Whether Deep Research and OpenAI's first agent, Operator, make their way into everyday lives is still up in the air. But with competition heating up, OpenAI isn't slowing down anytime soon.

ChatGPT's Deep Research tool can create reports from hundreds of online sources

There's no two ways about it, there's a newfound sense of urgency at OpenAI. Two days after releasing o3-mini to the world, the company made a surprise announcement on Sunday evening, revealing Deep Research. The new feature allows ChatGPT to find, analyze and synthesize hundreds of websites and online sources to create reports "at the level of a research analyst." On top of the usual text questions, users can upload files, including PDFs and spreadsheets, when prompting ChatGPT in this way. The chatbot will then take "anywhere from 5 to 30 minutes" to compile an answer, a side panel documenting the agent's progress and citations as it works. "It accomplishes in tens of minutes what would take a human many hours," OpenAI says of the new feature. "Our ultimate aspiration is a model that can uncover and discover new knowledge for itself," said Mark Chen, chief research officer at OpenAI, during the company's reveal livestream. "It's core to our [artificial general intelligence] roadmap." As far as limitations go, OpenAI says ChatGPT can sometimes hallucinate facts or make incorrect inferences when conducting Deep Research, though "at a notably lower" rate than other current models. Additionally, the agent may sometimes struggle to differentiate between authoritative information and rumors. Users may also notice some formatting errors. "We expect all these issues to quickly improve with more usage and time," the company notes. If all of this sounds familiar, it's because Google's Advanced suite includes its own Deep Research feature, which not only shares the same name but broadly offers the same set of capabilities as well. One significant difference between the two is that Google offers access to Gemini Advanced through its $20 per month One AI Premium plan. By contrast, you'll need a $200 per month ChatGPT Pro plan to start using OpenAI's version of Deep Research today. "Deep research in ChatGPT is currently very compute intensive," the company reasons, adding it will limit Pro users to 100 queries per month. "The longer it takes to research a query, the more inference compute is required." OpenAI says it's working on a version of Deep Research powered by a smaller, more cost-effective model. In turn, that will allow the company to offer "significantly higher rate limits." In the meantime, OpenAI hopes to get the tool in the hands of Plus users "in about a month," following a round of safety testing. As with most of the company's other recent releases, European users will need to wait before they can try out the tool for themselves, with Deep Research not yet available to people in the UK, Switzerland and the broader European economic zone.

OpenAI to offer deep research agent for ChatGPT

OpenAI today launched deep research in ChatGPT, a new agent that takes a little longer to perform a deeper dive into the web to come up with a response to a query. According to OpenAI, the new agent will "find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst." It uses a version of the company's upcoming o3 model to trawl the internet for information, pivoting as needed in reaction to what it encounters. It can take anywhere from five to 30 minutes to complete its work. OpenAI claimed: "It accomplishes in tens of minutes what would take a human many hours." OpenAI published a plethora of statistics to back up its claims. On the Humanity's Last Exam evaluation, a dataset of 3,000 questions across a hundred subjects designed to benchmark LLMs, OpenAI deep research managed an accuracy of 26.6 percent. By way of comparison, GPT-4o scored 3.3 percent, and Grok-2 managed 3.8 percent. Users will be forgiven for experiencing a jolt of déjà vu. Google rolled out Deep Research to Gemini Advanced subscribers on December 11, 2024, and claimed the technology would save users "hours of time." Google's Deep Research works by creating a multi-step research plan for a user to either revise or approve. Once given the go-ahead, the bot trawls the internet on the user's behalf. OpenAI's deep research is more geared for asking ChatGPT a question, perhaps adding additional resources such as spreadsheets for context, and then letting it run. The result includes citations and a summary of how the agent came up with its response. However, the onus remains on the user to reference and verify the information returned by the software. And verification continues to be necessary: OpenAI stated that inaccuracies and hallucinations occurred at a lower rate than existing ChatGPT models - according to the company's internal evaluations. "It may struggle with distinguishing authoritative information from rumors, and currently shows weakness in confidence calibration, often failing to convey uncertainty accurately." The deep research agent is only available for Pro users, who pay the company $200 per month. Plus and Team users will be added next, followed by Enterprise. One hundred queries per month are permitted, although OpenAI said that paid customers would soon get "significantly higher rate limits" as the company releases faster versions powered by a small model. The timing after the arrival of AI models from Chinese startup DeepSeek is interesting. DeepSeek has made claims about the models' greater efficiencies and performance. As for OpenAI? "Deep research in ChatGPT is currently very compute intensive," the US business said today. OpenAI's deep research agent is currently web-only, although there are plans to roll it out to mobile and desktop applications within the month. There is also the intent to allow customers to extend the agent's reach by connecting it to more specialized data sources. In the longer term, OpenAI envisages a combination of deep research and Operator, which can take real-world action, to "enable ChatGPT to carry out increasingly sophisticated tasks." ®

OpenAI Shows Off AI "Researcher" That Compiles Detailed Reports, Struggles to Differentiate "Information From Rumors"

OpenAI has unveiled a new research tool that can pull information from the web for you and summarize it into detailed reports -- supposedly "at the level of a research analyst." Naturally, major caveats to follow. Called "deep research," -- yes, without capitalization -- the tool is a type of AI agent, an industry term used to describe models that can perform tasks on your behalf. OpenAI released its first AI agent, Operator -- with the "O" capitalized -- only last month, showcasing its ability to shop for groceries and make reservations online. Catering towards higher-brow ambitions, OpenAI has built deep research for "intensive knowledge work" in fields like finance and science. But for those who like the idea of a bot doing their shopping, OpenAI says deep research, which is powered by an upcoming version of the company's o3 model, can help in that department by giving them "hyper-personalized" recommendations on big purchases like cars and appliances. "It accomplishes in tens of minutes what would take a human many hours," OpenAI claimed, by leveraging its reasoning capabilities to peruse text, images, and PDFs on the internet. Deep research is available only to those who are subscribed to the $200-per-month ChatGPT Pro plan. In addition to giving text responses like the chatbot normally does, the tool also features an activity sidebar that shows a step-by-step summary of its process in real time. Right now, its final reports are strictly text-based, but OpenAI says that images and data visualizations will be added in the coming weeks. Given that it's actually opening and looking through potentially enormous amounts of web content, responses can take anywhere from five to 30 minutes to produce, OpenAI said. But once you give it its instructions and answer some preliminary questions, you can step away, and the bot handles the rest. There's no guaranteeing the rigor of the research, however. Like all large language models, deep research can "sometimes" hallucinate -- or make up -- facts, OpenAI admitted, though the company claims the tool does this at a lower rate than its existing models. The AI agent also struggles with separating "authoritative information from rumors," and often fails to convey uncertainty. In other words: it has a bad habit of passing fiction off as fact. Impressive as the tech may be, those are huge drawbacks. We're not talking about a plain ol' chatbot anymore. We're talking about something explicitly geared towards serious knowledge gathering, even in scientific fields. Less leeway is permissible here. Deep research may be able to gather loads of information in a matter of minutes, but how much of it can be trusted? And how much time would you spend double-checking the accuracy of its synthesized report, and by extension the sources it cites? These are all questions worth asking as OpenAI rushes another AI out the door, after having a fire lit under it by DeepSeek.

OpenAI's Latest AI Agent Can Conduct Multi-Step Research on the Internet

Deep Research outputs can take between five to 30 minutes to generate OpenAI introduced a new artificial intelligence (AI) agent in ChatGPT on Sunday that can independently research on the Internet. Dubbed Deep Research (not to be confused with Google's Gemini-powered AI agent with the same name), it can conduct multi-step research on complex topics. The AI firm stated that the AI agent is powered by one of the o3 AI models and is currently available to the ChatGPT Pro users, the company's highest subscription tier. Notably, the announcement came just days after Google rolled out its Deep Research agent to the Gemini Android app. In a blog post, the San Francisco-based AI firm detailed its latest agentic capability in ChatGPT. Aimed at research-oriented tasks, OpenAI says it can complete tasks that would take a human multiple hours in tens of minutes. Deep Research joins the company's other AI agent dubbed Operator which can autonomously perform tasks online such as booking tickets, reserving a table in a restaurant, or buying a product. Highlighting when the AI agent might be useful, the company said that Deep Research is built for users who do intensive research-based work in areas such as finance, science, policy, and engineering. It is also aimed at users who prefer "hyper-personalised recommendations" on high-ticket purchases that generally require research such as cars, furniture, and home appliances. ChatGPT Pro users can find the Deep Research button underneath the text field next to the Search icon. Users can type their query and tap on the icon to activate the AI agent. The agent will respond with a follow-up request, asking for details about the users' preferences and more details about their requirements. Users can also add a file to provide it with more context. After responding to the follow-up request, the AI agent will begin researching, with a thin bar showing the progress. A sidebar will also appear with a summary of the steps taken and sources used. The output can take between five to 30 minutes, and the user will get a comprehensive report once the research is done. Powered by a version of the o3 model, the AI agent will use citations wherever information is taken from a particular source. It will also use tables and sub-headings to make the report readable. OpenAI says in the next few weeks, the company will add support for images, data visualisation, and other analytic output in these reports. Currently, it is only available to ChatGPT Pro subscribers, but the company said it will soon be added to the Plus and Teams subscriptions. Notably, the Pro subscription is priced at $200 (roughly Rs. 17,500) a month.

OpenAI launches ChatGPT DeepResearch - 5 things you need to know

OpenAI just dropped ChatGPT DeepResearch, and if you're someone who spends hours digging through endless sources for research, this might be the tool you've been waiting for. Designed to streamline and automate complex, multi-step research tasks, DeepResearch leverages OpenAI's latest o3-mini model to scan, analyse, and synthesize information from all over the internet. It's like having an AI-powered research assistant that can put together well-structured reports in record time. Here's a look at what makes it stand out. One of the coolest things about DeepResearch is its ability to handle entire research processes on its own. You don't just throw a question at it and get a generic AI-generated response - it actually plans how to tackle your query step by step. Whether you feed it text, PDFs, images, or spreadsheets, the system maps out a multi-step research strategy, pulls in data from different sources, and delivers a structured report in about 5 to 30 minutes. The main aim is to facilitate a smoother workflow for folks whose jobs revolve around doing research in a way that makes sense. The AI doesn't just scrape results and regurgitate them; it processes and synthesizes information, giving you something closer to what an actual researcher would put together. Also Read: AMD's Jaya Jagadish: India to play 'transformative role' in global AI, datacenter and chip landscape DeepResearch is using OpenAI's new o3-mini, a version of the upcoming o3-series designed specifically for browsing and data analysis. That means it's better at filtering through the vast, messy world of the internet, finding useful content, and piecing it together into a coherent analysis. Unlike older AI models that sometimes fumble when asked to verify sources or follow logical chains, o3-mini is optimized to handle multi-step reasoning and structured research. This is what allows DeepResearch to actually "think through" research problems instead of just returning the first five search results it finds. For now, DeepResearch is available on the web version of ChatGPT, but OpenAI has plans to roll it out on mobile and desktop versions later this month. This means you'll soon be able to run full-fledged research sessions right from your phone or laptop without needing to be tethered to a browser. This is a big deal, especially for professionals who need to do research on the go. Imagine being able to dump a set of PDFs into the app while commuting and getting a summarized, cited report by the time you arrive at work. That's where this is headed. Also Read: CloudMosa Cloud Phone: The feature phone that's rewriting the rules of connectivity As impressive as DeepResearch is, it's not infallible. OpenAI is upfront about the fact that the tool can sometimes misinterpret data or pull in unreliable sources. Unlike a human researcher who can tell the difference between a well-respected academic journal and a random blog post, AI still struggles with evaluating credibility. It also has a tough time conveying uncertainty. Sometimes, research topics are just gray areas with no clear-cut answers, and DeepResearch might present uncertain findings with more confidence than it should. That means users will still need to apply some human judgment and double-check key details - this is an AI assistant, not a fully autonomous researcher. DeepResearch is being launched as a feature for OpenAI's Pro users, and it comes with a hefty price tag - $200 per month for 100 queries. That puts it squarely in the hands of serious researchers, analysts, and businesses rather than casual users. That said, OpenAI is reportedly working on a faster, more optimized version that might offer better pricing models in the future. For now, if you're dealing with research-heavy workflows - like market analysis, legal research, or academic studies - this could be worth the investment. Also Read: Best gaming PC under ₹1,00,000 in January 2025: CPU, GPU, Motherboard, RAM, PSU, Storage, and Cabinet DeepResearch is a major step forward for AI-driven research. It's not just another chatbot that spits out quick answers; it actually digs through sources, processes data, and compiles structured insights, or at least that is what OpenAI is claiming. While it's not perfect and still requires human oversight, it has the potential to save countless hours for professionals who need reliable information, fast. The big question now is how OpenAI refines it over time - because if they can improve its ability to verify sources and convey uncertainty better, we might be looking at one of the most powerful research tools ever built.

OpenAI's 'Deep Research' Aims to Impact Business Intelligence | PYMNTS.com

OpenAI's new "Deep Research" tool is poised to transform how businesses gather intelligence and shape their corporate strategy, according to experts. But it does come with some key caveats. Deep Research is an artificial intelligence (AI)-driven research assistant that can search the web for in-depth information about a topic and then generate a detailed report at the level of a research analyst in "tens of minutes," according to OpenAI, which publicly demonstrated the tool on Sunday (Feb. 2). "It is particularly effective at finding niche, non-intuitive information that would require browsing numerous websites," OpenAI said in a blog post. "Deep Research frees up valuable time by allowing you to offload and expedite complex, time-intensive web research with just one query." OpenAI Chief Research Officer Mark Chen said in a YouTube video that Deep Research is one step closer to the company's goal of achieving artificial general intelligence or AGI. That's when machines reach human-level intelligence and can broadly apply that knowledge across a range of tasks. But OpenAI is aiming even beyond it: "Our ultimate aspiration is a model that can uncover and discover new knowledge for itself," Chen said. Deep Research is now available through ChatGPT. It has been rolled out to Pro users with a cap of 100 queries a month, with Plus and Team users getting it next, followed by Enterprise accounts. OpenAI will raise the cap once it develops a faster and cheaper version of Deep Research. "OpenAI's Deep Research tool can change the way companies conduct research by performing complicated tasks fast and efficiently. It can scan the internet, collect data, and generate thorough reports in a matter of minutes -- tasks that would take human researchers hours to complete," Sergio Oliveira, director of development at DesignRush, told PYMNTS. "Businesses can use it for market research, evaluating potential business partners, or keeping up with new technology and trends," Oliveira said. "The primary advantage is speed. It saves time, provides a broad overview of subjects and lowers expenses by decreasing the requirement for manual research." Peter Morales, CEO of Code Metal, added that Deep Research's agentic workflow is "valuable" and a natural fit for industry verticals. For example, in pharmaceuticals, an analyst tasked with creating a report on drug interactions and usage data for a specific drug would start by querying the web or drug databases for known variants of the drug, Morales told PYMNTS. Then, the analyst would manually research and correlate data on interactions and usage for each of these variants. "This entire activity can now be automated" by Deep Research, Morales said. In marketing, Deep Research lets a company "streamline the voice of the customer and competitor research," Colby Flood, founder of Brighter Click, told PYMNTS. Flood said this process normally entails gathering content from competitors' websites and manually reviewing it to understand the rational and emotional motivators used to attract customers; and then compiling customer reviews to analyze sentiment and determine what customers like or don't like about your and your competitors' products. "It also entails scraping text from sites like Reddit to understand the general market consensus," Flood said. Now, Deep Research "could eliminate the need for many expensive social listening tools by providing an out-of-the-box AI solution." Alexey Chyrva, Chief Product Officer of Kitcast, told PYMNTS that Deep Research benefits businesses by offering efficiency and accessibility. Importantly, its research also can help "ensure that new products or features don't violate existing intellectual property. That will save companies from possible lawsuits and other problems." But like all early experimental tools, it comes with caveats. Deep Research can "sometimes hallucinate" or make "incorrect inferences," though less than current ChatGPT models, OpenAI said. Deep Research may also "struggle with distinguishing authoritative information from rumors and ... often failing to convey uncertainty accurately." Chyrva noted that this weakness in separating fact from rumors "affects the reliability of those reports." Deep Research also "struggles with conveying uncertainty, which may lead to overconfidence in the findings," he said. Nathan Brunner, CEO of Boterview, tested Deep Research and said it was an "excellent" tool for gathering statistics and facts. However, he noticed that the results are "only as good as the websites it gets information from," which could include less reliable sources. After Deep Research generates a report, it is "always crucial to have someone verify that the sources are reliable and not random forums," Brunner told PYMNTS.com. Over time, Brunner is concerned that the quality of the content would decline if websites decide to block these AI agents because they are not getting any compensation. Morales summed it up this way: "Deep Research has some of the inherent limitations of being non-deterministic that exists for generative AI. Additionally, in the successive refinement steps, it is unable to assess the reliability of information sources. This may cause it to produce unreliable data where there is a preponderance of non-authoritative sources."

OpenAI's 'deep research' tool: is it useful for scientists?

Tech giant OpenAI has unveiled a pay-for-access tool called 'deep research', which synthesizes information from dozens or hundreds of websites into a cited report several pages long. The tool follows a similar one from Google released in December and acts as a personal assistant, doing the equivalent of hours of work in tens of minutes. Many scientists who have tried it are impressed with its ability to write literature reviews or full review papers and even identify gaps in knowledge. Others are less enthusiastic. "If a human did this I would be like: this needs a lot of work," says Kyle Kabasares, a data scientist at the Bay Area Environmental Research Institute in Moffett Field, California, in an online video review. The firms are presenting the tools as a step towards AI 'agents' that can handle complex tasks. Observers say that OpenAI's deep research tool, released on 2 February, is notable because it combines the improved reasoning skills of the o3 large language model (LLM) with the ability to search the Internet. Google says its Deep Research tool is, for now, based on Gemini 1.5 Pro, rather than on its leading reasoning model 2.0 Flash Thinking. Many users are impressed with both tools. Andrew White, a chemist and AI expert FutureHouse, a start-up in the San Francisco, California, says that Google's product is "really leveraging Google's advantages in search and compute" to get users up to speed on a topic quickly, while o3's reasoning skills add sophistication to OpenAI's reports. Derya Unutmaz, an immunologist at the Jackson Laboratory in Farmington, Connecticut, who has free access to ChatGPT Pro granted by OpenAI for medical research, says the OpenAI deep research reports are "extremely impressive", "trustworthy" and as good or better than published review papers. "I think writing reviews is becoming obsolete." White anticipates that AI systems like these could be used to update human-authored reviews. "Authoritative reviews cannot feasibly be updated [by humans] every 6 months.". But many caution that all LLM-based tools are sometimes inaccurate or misleading. OpenAI's website admits that its tool "is still early and has limitations": it can get citations wrong, hallucinate facts, fail to distinguish authoritative information from rumors and fail to convey its uncertainty accurately. The company expects the issues to improve with more usage and time. Google's Deep Research has a disclaimer that simply reads "Gemini can make mistakes, so double-check it". These tools are not doing "research" in the sense that scientists usually use the term, notes Mario Krenn, leader of the Artificial Scientist Lab at the Max Planck Institute for the Science of Light in Erlangen, Germany. Scientists, he says, spend years investigating a single topic and evolving new ideas. "This ability has not been demonstrated [by AI] yet," Krenn says, adding "maybe it will be soon, one never knows these days." OpenAI has put its deep research tool through its paces. It fared well, for example, on Humanity's Last Exam (HLE), a 3,000-question benchmark test that covers expert-level knowledge across topics from linguistics to science and was designed to be much harder for LLMs than other common tests that are now bested by AI, such as the GPQA. OpenAI's product tops the chart with 26.6% on the text-only questions of the HLE. The firm also tested its system against the GAIA benchmark, developed in 2023 to test AI that uses multi-step reasoning and web browsing to answer questions. The public GAIA leaderboard is headed by an agent from global company H2O.ai powered by Claude 3.5 Sonnet from San Francisco company Anthropic, with a hardest-level score of 40.82%. OpenAI's deep research scored 58.03%. Google says it does not have any benchmarking results to share for its tool. The benchmarks chosen by OpenAI rely on questions that have short, verifiable answers, which might not be well suited to tools that generate long answers with no specifically correct response, says White. "I think these benchmarks are going to fade away in favour of functional benchmarks," he says, such as human evaluations of the quality and utility of articles. White previously worked on a paper, for example, in which human experts blindly graded statements taken from AI-written and human-written Wikipedia-style summaries of scientific topics; the AI won. Both products have other limitations. OpenAI's tool isn't available to users in the European Union, United Kingdom or Switzerland as the company navigates regulations. Google's Deep Research is available in more than 150 countries. And neither can extract paywalled information, which includes many scientific papers. This "is a major, major issue," says Unutmaz, who is a proponent of open science. "Accessing this knowledge is more important than ever," he says. Some scientists have proposed in online forums that they should be able to plug their journal passwords into AI tools, and have speculated about using OpenAI's new 'operator' agent to do this. OpenAI's CEO Sam Altman has tweeted in response: "We do need to figure something out here."

OpenAI Launches Deep Research: AI Agent for In-Depth Web Analysis

Future updates will include data visualisations and embedded images. OpenAI has introduced a new deep research capability in ChatGPT, which the company describes as a new agentic capability that conducts multi-step research on the internet for complex tasks. According to OpenAI, the new AI agent uses reasoning to synthesise large amounts of online information and complete multi-step research tasks for users. "It accomplishes in tens of minutes what would take a human many hours," OpenAI said on February 2, 2025. Also Read: OpenAI's ChatGPT Service Only Disseminates Public Information: Report OpenAI Founder Sam Altman announced the launch on microblogging site X, stating, "Today we launch deep research, our next agent....this is like a superpower; experts on demand..it can go use the internet, do complex research and reasoning, and give you back a report...it is really good, and can do tasks that would take hours/days and cost hundreds of dollars." "You give it a prompt, and ChatGPT will find, analyse, and synthesise hundreds of online sources to create a comprehensive report at the level of a research analyst," OpenAI explained. Powered by an optimised version of OpenAI's upcoming O3 model, Deep Research independently searches, Interprets, analyses, and synthesises vast amounts of online data -- including text, images and PDFs -- making it a valuable tool for professionals in finance, science, policy, and engineering, according to the company. "The ability to synthesise knowledge is a prerequisite for creating new knowledge. For this reason, deep research marks a significant step toward our broader goal of developing AGI (Artificial General Intelligence), which we have long envisioned as capable of producing novel scientific research," OpenAI added. "It can be equally useful for discerning shoppers looking for hyper-personalised recommendations on purchases that typically require careful research, like cars, appliances, and furniture," the Microsoft-backed company said. Unlike standard AI responses, Deep Research delivers fully documented reports with clear citations and reasoning summaries, ensuring reliability. Users can request detailed analyses -- ranging from competitive market insights to personalised shopping recommendations -- by selecting the Deep Research option in ChatGPT. The tool autonomously browses the web, adapts its search based on findings, and compiles a comprehensive report, which may take 5 to 30 minutes to complete. OpenAI positions Deep Research as a bridge between quick AI summaries and in-depth, verifiable analysis, marking a significant step toward Artificial General Intelligence (AGI). Future updates will introduce embedded images, data visualisations, and richer analytic outputs for enhanced clarity. Kevin Weil, OpenAI's Chief Product Officer, highlighted the tool's capabilities at the Washington event, stating, "It can handle complex research tasks that might typically take a person anywhere from 30 minutes to 30 days." Deep Research can complete such tasks in as little as five to 30 minutes, depending on complexity. Also Read: OpenAI Announcements in December 2024: From ChatGPT Pro to Sora Explaining limitations, OpenAI noted that Deep research can sometimes hallucinate facts in responses or make incorrect inferences, though at a notably lower rate than existing ChatGPT models, according to internal evaluations. It may struggle with distinguishing authoritative information from rumours, and currently shows weakness in confidence calibration, often failing to convey uncertainty accurately. "Deep research in ChatGPT is currently very compute intensive. The longer it takes to research a query, the more inference compute is required," the company said. Initially, the model will be accessible to OpenAI's USD 200-a-month Pro users with up to 100 queries per month, with plans to extend availability to the USD 20-a-month Plus tier and Team users, followed by Enterprise, pending safety evaluations within the next month. OpenAI said the company is still working on bringing access to users in the United Kingdom, Switzerland, and the European Economic Area. Deep research is available now on ChatGPT web and will be rolled out to mobile and desktop apps within the month. This launch follows the recent release of another OpenAI tool capable of performing online tasks like grocery shopping and restaurant reservations.

OpenAI's newest ChatGPT agent can do 'deep research' online

OpenAI has released a new agent for its flagship artificial intelligence product ChatGPT called "deep research," which can trawl the internet for information to create a report "at the level of a research analyst." OpenAI said in a Feb. 2 blog post that deep research was "built for people who do intensive knowledge work in areas like finance, science, policy, and engineering and need thorough, precise, and reliable research." The company added that it's also useful for research before buying big-ticket items like cars or appliances, and the outputs -- which can take anywhere from 5 to 30 minutes -- are "fully documented, with clear citations and a summary of its thinking." The latest agent follows OpenAI's Jan. 23 launch of Operator, a ChatGPT agent that can use the internet to complete tasks like ordering groceries and booking holiday tours. It also comes about a week after the AI space and US tech stocks were rocked by a new AI model from the China-based DeepSeek that reportedly performed as well as ChatGPT but was developed for a fraction of the cost. Microsoft and OpenAI are reportedly probing if data from ChatGPT's API was improperly obtained by a group linked to DeepSeek. OpenAI said its deep research agent scored a new high on the AI evaluation called Humanity's Last Exam, which has 3,000 expert-level questions on over 100 topics, achieving an accuracy of 26.6% compared to a score of 9.4% for DeepSeek-R-1 and 3.3% for its own GPT-4o model. Related: DeepSeek privacy concerns raise international alarm bells The agent is powered by the OpenAI o3 model but "optimized for web browsing and data analysis." OpenAI o3 is the firm's latest "reasoning model," which attempts to essentially fact-check itself to avoid getting facts wrong or generating false information. OpenAI warned that deep research "can sometimes hallucinate facts in responses or make incorrect inferences" and can "struggle with distinguishing authoritative information from rumors." Last month, Google announced it was rolling out a similar feature, also called "Deep Research" for its AI model Gemini in early 2025, while OpenAI said its agent is now available on its $200-a-month Pro plan, limited to 100 queries a month.

ChatGPT just got OpenAI's most powerful upgrade yet -- meet 'Deep Research'

Artificial intelligence has already begun to change the way we conduct research, and now OpenAI just released a fresh update to ChatGPT that, it says, will open up "deep research" to just about anyone. Following just days after its 03-mini reasoning model, the new deep research tool is launching today for ChatGPT Pro subscribers. "Today we're launching deep research in ChatGPT, a new agentic capability that conducts multi-step research on the internet for complex tasks," a blog post reads, promising that the model "accomplishes in tens of minutes what would take a human many hours." This new agent "can do work for you independently", acting on a series of prompts to "find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst". It's powered by the upcoming o3 model of ChatGPT and is geared towards finance, science, policy and engineering research, while OpenAI also says that it can helpful for making purchasing decisions, too, helping run detailed product research (another shot across Google's bow, perhaps). Using the new tool is simple, too. Users just need to select 'deep research' in the ChatGPT message composer and enter the query, with the option to attach additional context via files and spreadsheets. Doing so will see articles cited in the sidebar, and the progress can be tracked there too. OpenAI says it can take five minutes to half an hour to complete a deep research task. OpenAI has stressed that there are limitations, however. "It can sometimes hallucinate facts in responses or make incorrect inferences, though at a notably lower rate than existing ChatGPT models, according to internal evaluations." "It may struggle with distinguishing authoritative information from rumors, and currently shows weakness in confidence calibration, often failing to convey uncertainty accurately. At launch, there may be minor formatting errors in reports and citations, and tasks may take longer to kick off. We expect all these issues to quickly improve with more usage and time." Still, if you want to give it a whirl, you can do so today -- providing you're paying for ChatGPT Pro.

OpenAI's new ChatGPT agent is 'like a superpower,' says CEO Sam Altman

OpenAI has just announced a new AI tool called Deep Research. The new AI agent is capable of conducting multi-step research on the internet for complex tasks and, according to OpenAI, "accomplishes in tens of minutes what would take a human many hours." You simply give it a prompt and ChatGPT will "find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst." OpenAI demonstrated the new feature in a video shared on Sunday (above). Deep Research caters to professionals in finance, science, policy, and engineering, providing thorough, reliable insights. It's also beneficial for shoppers seeking personalized recommendations on purchases that require careful research, like those for cars, appliances, and furniture. Outputs include clear citations and summaries, enabling easy verification. Essentially, the feature streamlines time-consuming research, delivering niche information efficiently from a single query. In a flurry of posts shared on X on Sunday, OpenAI chief Sam Altman described Deep Research as being "like a superpower; experts on demand." He said it can "go use the internet, do complex research and reasoning, and give you back a report," taking care of tasks "that would take hours/days and cost hundreds of dollars." While it's "very compute-intensive and slow," he claimed that "it's the first AI system that can do such a wide variety of complex, valuable tasks." Deep Research takes between 5 and 30 minutes to complete its work, and you'll receive a notification once the research is complete. The final output arrives as a report, delivered by ChatGPT. At the moment, reports are text-only, but OpenAI said that in the coming weeks it'll be adding embedded images, data visualizations, and other analytic outputs for additional clarity and context. Deep Research is now available as part of OpenAI's Pro tier ($200 a month), with 100 queries available per month on the web (coming to mobile and desktop apps by the end of February). It'll also arrive for Plus, Team, and Enterprise customers "soon," before eventually making its way to OpenAI's free tier. Altman urged people to "give it a try on your hardest work task that can be solved just by using the internet and see what happens." But take note: OpenAI cautioned the its new tool "may struggle with distinguishing authoritative information from rumors, and currently shows weakness in confidence calibration, often failing to convey uncertainty accurately." It added that, at launch, you might also see "minor" formatting errors in reports and citations, and tasks may take longer to kick off. "We expect all these issues to quickly improve with more usage and time," OpenAI said. Deep Research arrives just a week after OpenAI unveiled another AI agent, called Operator, which acts like a human assistant, performing web-based tasks like making reservations, booking trips, and ordering groceries, in line with your requests.

OpenAI unveils a new ChatGPT agent for 'deep research' | TechCrunch

OpenAI is announcing a new AI "agent" designed to help people conduct in-depth, complex research using ChatGPT, the company's AI-powered chatbot platform. OpenAI said in a blog post published Sunday that these this new capability was designed for "people who do intensive knowledge work in areas like finance, science, policy, and engineering and need thorough, precise, and reliable research." It could also be useful, the company added, for anyone making "purchases that typically require careful research, like cars, appliances, and furniture." Basically, ChatGPT deep research is intended for instances where you don't just want a quick answer or summary, but instead need to assiduously consider information from multiple websites and other sources. OpenAI said it's making deep research available to ChatGPT Pro users today, limited to 100 queries per month, with support for Plus and Team users coming next, followed by Enterprise. (OpenAI is targeting a Plus rollout in about a month from now, the company said.) It's a geo-targeted launch; OpenAI had no release timeline to share for ChatGPT customers in the U.K., Switzerland, and the European Economic Area. To use ChatGPT deep research, you'll just select "deep research" in the composer and then enter a query, with the option to attach files or spreadsheets. (It's a web-only experience for now, with mobile and desktop app integration to come later this month.) Deep research could then take anywhere from 5 to 30 minutes to answer the question, and you'll get a notification when the search completes. Currently, ChatGPT deep research's outputs are text-only. But OpenAI said that it intends to add embedded images, data visualizations, and other "analytic" outputs soon. Also on the roadmap is the ability to connect "more specialized data sources," including "subscription-based" and internal resources, OpenAI added. The big question is, just how precise is ChatGPT deep research? AI is imperfect, after all. It's prone to hallucinations and other types of errors that could be particularly harmful in a "deep research" scenario. That's perhaps why OpenAI said every ChatGPT deep research output will be "fully documented, with clear citations and a summary of [the] thinking, making it easy to reference and verify the information." The jury's out on whether those mitigations will be sufficient to combat AI mistakes. OpenAI's AI-powered web search feature in ChatGPT, ChatGPT Search, not infrequently makes gaffes and gives wrong answers to questions. TechCrunch's testing found that ChatGPT Search produced less useful results than Google Search for certain queries. To beef up deep research's accuracy, OpenAI is using a special version of its recently announced o3 "reasoning" AI model that was trained through reinforcement learning on "real-world tasks requiring browser and Python tool use." Reinforcement learning essentially "teaches" a model via trial and error to achieve a specific goal. As the model gets closer to the goal, it receives virtual "rewards" that, ideally, make it better at the task going forward. OpenAI claimed that, thanks to the fine-tuned o3 model, deep research can perform multi-step research, backtrack and react to real-time information, generate graphs, and specifically cite "hundreds" of sources and passages. "[This] version of the upcoming OpenAI o3 model [is] optimized for web browsing and data analysis," OpenAI said in the blog. "[I]t leverages reasoning to search, interpret, and analyze massive amounts of text, images, and PDFs on the internet, pivoting as needed in reaction to information it encounters [...] The model is also able to browse over user uploaded files, plot and iterate on graphs using the python tool, embed both generated graphs and images from websites in its responses, and cite specific sentences or passages from its sources." The company said that it tested ChatGPT deep research using Humanity's Last Exam, an evaluation that includes more than 3,000 expert-level questions in a variety of academic fields. The o3 model powering deep research achieved an accuracy of 26.6%, which might look like a failing grade -- but Humanity's Last Exam was designed to be tougher than other benchmarks to stay ahead of model advancements. According to OpenAI, the deep research o3 model came in way ahead of Gemini Thinking (6.2%), Grok-2 (3.8%), and OpenAI's own GPT-4o (3.3%). Still, OpenAI notes that ChatGPT deep research has limitations, sometimes making mistakes and incorrect inferences. Deep research may struggle to distinguish authoritative information from rumors, the company said, and often fails to convey when it's uncertain about something -- and it can also make formatting errors in reports and citations. For anyone worried about the impact of generative AI on students, or on anyone trying to find information online, this type of in-depth, well-cited output probably sounds more appealing than a deceptively simple chatbot summary with no citations. But we'll see whether most users will actually subject the output to real analysis and double-checking, or if they simply treat it as a more professional-looking text to copy-paste. And if this all sounds familiar, Google actually announced a similar AI feature with the exact same name less than two months ago.

Unlock the Power of OpenAI Deep Research AI to Transform Your Explorative Workflows

Research can be exhilarating -- diving into new topics, uncovering hidden insights, and piecing together the puzzle of knowledge. But let's be honest: it can also be overwhelming. The sheer volume of data, the pressure to stay current, and the challenge of tackling increasingly niche or complex topics can leave even the most passionate researchers feeling stretched thin. If you've ever wished for a way to spend less time on repetitive tasks and more time on the parts of research that truly excite you, you're not alone. The good news? OpenAI has recently made available its new Deep Research AI platform designed to transform how we approach research. Imagine having a tool that not only helps you sift through mountains of information but also summarizes it, provides context, and ensures your data is credible -- all while freeing up your time for deeper thinking and creativity. Deep Research is doing just that. An AI agent that uses reasoning to synthesize large amounts of online information and complete multi-step research tasks for you. Deep Research is currently being rolled out by OpenAI and is available to Pro users now, and will soon be available to ChatGPT Plus and Team subscribers. AI-powered tools are redefining how research is conducted by processing vast amounts of data, identifying patterns, and delivering actionable insights in a fraction of the time traditional methods require. These tools are particularly effective in tackling large-scale challenges. For example, AI algorithms can analyze global trends, such as the semiconductor chip shortage, offering valuable insights for policymakers and industry leaders. By automating repetitive tasks like data collection, organization, and preliminary analysis, AI allows you to dedicate more time to critical thinking and problem-solving. Moreover, AI tools are adaptable across disciplines, from social sciences to engineering, allowing researchers to explore new dimensions of their fields. Whether you're investigating climate change, market trends, or medical advancements, AI provides the computational power to uncover patterns and correlations that might otherwise go unnoticed. Data analysis is a cornerstone of research, and AI has transformed this domain by allowing faster, more accurate processing of complex datasets. Machine learning models can sift through large volumes of data, identifying correlations, anomalies, and trends with remarkable precision. For instance, if you're studying regional economic patterns, AI can analyze geographic-specific data to uncover localized insights that inform policy or investment decisions. In fields like healthcare, AI can analyze patient data to identify risk factors for diseases, while in finance, it can detect market anomalies to guide investment strategies. These capabilities not only improve the quality of your findings but also open up opportunities for data-driven decision-making. By using AI, you can transform raw data into meaningful insights, driving innovation and advancing your research objectives. AI plays a pivotal role in automating research workflows, reducing the time and effort required for routine tasks. Literature reviews, citation management, and project tracking can all be streamlined using AI-powered tools. For example, AI can quickly scan thousands of academic papers to identify the most relevant studies, saving you hours of manual effort. Similarly, tools like automated citation generators ensure that your references are accurate and properly formatted. By automating these repetitive activities, you can focus on higher-value tasks, such as hypothesis development, data interpretation, and strategic planning. Additionally, AI minimizes the risk of human error, making sure that your research process is both efficient and reliable. This enhanced productivity allows you to allocate more resources to exploring innovative ideas and addressing complex research questions. Here is a selection of other guides from our extensive library of content you may find of interest on AI research. Summarizing complex information is a time-intensive challenge, but AI tools simplify this process by generating concise, contextually relevant summaries. Whether you're reviewing academic papers, analyzing industry reports, or synthesizing findings from multiple sources, AI algorithms can extract key points and present them in an easily digestible format. This capability is particularly useful for niche research topics, where understanding the broader context is critical for drawing meaningful conclusions. For example, AI can summarize the findings of multiple studies on renewable energy technologies, helping you identify trends and gaps in the literature. By providing clear and concise summaries, AI enables you to stay informed without becoming overwhelmed by the sheer volume of available information. The credibility of your research depends on the reliability of its data, and AI tools excel at evaluating the trustworthiness of information. By cross-referencing multiple sources and identifying inconsistencies, AI ensures that your research is built on verified, high-quality data. For instance, when investigating industry-specific trends, AI can highlight the most reputable studies and reports, saving you time while enhancing the credibility of your findings. This capability is particularly valuable in an era of information overload, where distinguishing between reliable and unreliable sources can be challenging. By using AI, you can ensure that your research is grounded in accurate and trustworthy information, strengthening the validity of your conclusions and recommendations. AI fosters a culture of continuous learning by keeping your research up-to-date with the latest information and insights. As new data becomes available, AI tools can update your findings in real-time, making sure that your work remains relevant and accurate. This adaptability is essential in fast-evolving fields, where staying informed is critical for maintaining a competitive edge. For example, in fields like biotechnology or artificial intelligence itself, where advancements occur rapidly, AI tools can help you stay ahead by providing real-time updates on emerging trends and discoveries. By embracing AI, you can cultivate a mindset of curiosity and lifelong learning, driving innovation and making sure that your research remains at the forefront of your discipline. Integrating AI into your research practices offers significant benefits in terms of efficiency and effectiveness. By automating repetitive tasks, providing advanced data analysis capabilities, and making sure the credibility of your data sources, AI allows you to focus on the strategic aspects of your work. This not only accelerates the research process but also enhances the quality and relevance of your results. Whether you're exploring niche topics or addressing global challenges, AI enables you to achieve more in less time. Its ability to process complex data, streamline workflows, and provide actionable insights makes it an indispensable tool for modern researchers. By using AI, you can unlock new possibilities, drive innovation, and contribute to the advancement of knowledge in your field.

OpenAI launches 'deep research' tool after China's DeepSeek shakes AI world; Here's how to use new feature, limitations and more

OpenAI has launched 'deep research,' a new ChatGPT tool capable of generating detailed reports, as competition in the AI field intensifies with China's DeepSeek. The tool, announced in Tokyo, offers extensive exploration and citation for complex inquiries, taking 5 to 30 minutes to complete its analysis.Amid high stakes AI battle post China's entry with Deepseek, Sam Altman's OpenAI has launched a ChatGPT tool called "deep research" that can produce detailed reports, as China's DeepSeek chatbot heats up competition in the AI field. The company made the announcement in Tokyo, where OpenAI chief Sam Altman also trumpeted a new joint venture with tech investor SoftBank Group to offer advanced artificial intelligence services to businesses. How to use the new feature? In ChatGPT, select 'deep research' in the message composer and enter your query. Tell ChatGPT what you need -- whether it's a competitive analysis on streaming platforms or a personalized report on the best commuter bike. You can attach files or spreadsheets to add context to your question. Once it starts running, a sidebar appears with a summary of the steps taken and sources used. Deep research may take anywhere from 5 to 30 minutes to complete its work, taking the time needed to dive deep into the web. In the meantime, you can step away or work on other tasks -- you'll get a notification once the research is complete. The final output arrives as a report within the chat - in the next few weeks, we will also be adding embedded images, data visualizations, and other analytic outputs in these reports for additional clarity and context. Compared to deep research, GPT-4o is ideal for real-time, multimodal conversations. For multi-faceted, domain-specific inquiries where depth and detail are critical, deep research's ability to conduct extensive exploration and cite each claim is the difference between a quick summary and a well-documented, verified answer that can be usable as a work product. How does it works? Deep research was trained using end-to-end reinforcement learning on hard browsing and reasoning tasks across a range of domains. Through that training, it learned to plan and execute a multi-step trajectory to find the data it needs, backtracking and reacting to real-time information where necessary. The model is also able to browse over user uploaded files, plot and iterate on graphs using the python tool, embed both generated graphs and images from websites in its responses, and cite specific sentences or passages from its sources. As a result of this training, it reaches new highs on a number of public evaluations focused on real-world problems. What are the limitations? Deep research unlocks significant new capabilities, but it's still early and has limitations. It can sometimes hallucinate facts in responses or make incorrect inferences, though at a notably lower rate than existing ChatGPT models, according to internal evaluations. It may struggle with distinguishing authoritative information from rumors, and currently shows weakness in confidence calibration, often failing to convey uncertainty accurately. At launch, there may be minor formatting errors in reports and citations, and tasks may take longer to kick off. We expect all these issues to quickly improve with more usage and time.

ChatGPT's New 'Deep Research' AI Agent Brings OpenAI Closer to AGI

The Deep Research AI agent is built on the new o3 reasoning model. With web access, it scored 26.6% on Humanity's Last Exam. Another day, another AI agent. After the Operator AI agent, OpenAI has now released a new AI agent called 'Deep Research' on ChatGPT that goes to the web to do "research" for you independently. OpenAI says the Deep Research AI agent on ChatGPT can browse the web, find accurate sources, analyze them, and create a comprehensive report for you. It can take 5 to 30 minutes to perform deep research for you. ChatGPT's Deep Research agent is very similar to Gemini's Deep Research feature. The most noteworthy change is that Deep Research is based on the new OpenAI o3 model for web browsing and Python analysis. Thanks to the advanced reasoning capability of the o3 model, Deep Research can intelligently analyze PDFs, images, and text on the web. As a result, when o3 is given web access (+ Python tools) to do deep research, it scores 26.6% on Humanity's Last Exam -- a new rigorous benchmark consisting of challenging questions from domain experts around the world. o3-mini-high without web access only scores 13% and the new DeepSeek R1 model gets 9.4%. Currently, Deep Research is only available to users (100 queries per month) who are subscribed to the ChatGPT Pro plan, which costs $200 per month. OpenAI says Deep Research is coming soon to ChatGPT Plus (10 queries per month), Team, Enterprise, and free users too. OpenAI further says Deep Research is "built for people who do intensive knowledge work in areas like finance, science, policy & engineering and need thorough & reliable research." With the release of Deep Research, OpenAI CEO Sam Altman suggested that this AI agent can perform "a single-digit percentage of all economically valuable tasks in the world". This statement aligns with OpenAI's definition of AGI in its charter -- "highly autonomous systems that outperform humans at most economically valuable work." It seems OpenAI is hinting that we are coming close to achieving AGI. Now we need to check how accurate and reliable the new Deep Research agent is. So stay tuned for our analysis.

OpenAI's ChatGPT can now perform comprehensive research for its users - SiliconANGLE

OpenAI's ChatGPT can now perform comprehensive research for its users OpenAI has announced a new "agentic" feature for ChatGPT that enables it to conduct intensive and complex research on behalf of users. The new capability, called "deep research" was announced by the company in a blog post Sunday, where it said it's able to operate autonomously, planning and executing multi-step trajectories to find the information requested by users. It's said to be capable of "backtracking and reacting to real-time information" whenever it's necessary. When a user asks deep research to investigate something, they won't just be given a straightforward, text-based answer. Instead, ChatGPT will show a summary of its research process in a sidebar, complete with citations that reference its findings. Users will be able to ask questions using simple text and upload images and other files such as PDFs and spreadsheets to provide context. ChatGPT will then take anywhere from five minutes to 30 minutes to generate a comprehensive response. In future, it will also be able to respond with embedded charts and images, the company said. OpenAI said ChatGPT deep research is akin to having a professional human researcher, but it warned that AI can still make mistakes, with risks including it making up facts, struggling to tell the difference between rumors and authoritative information, and rating certain responses. The company is trying to limit these "hallucinations" with the use of a specialized version of its newly announced "reasoning" model o3-mini, which has been trained using reinforcement learning techniques, where it performs real-world tasks using a browser and Python tools. Reinforcement learning is a technique that enables AI models to learn through trial and error to work out the best way to achieve specific goals. As the model gets closer to its goal, it will receive virtual rewards that motivate it to complete the task more efficiently. According to OpenAI, the version of o3 used in deep research has been optimized for web browsing and data analysis tasks. It explained that the model uses its reasoning abilities to search through, interpret and analyze massive amounts of text, images and other data on the internet, and then pivot in response to what it learns from that analysis. ChatGPT deep research qualifies as "agentic AI", which refers to more sophisticated AI tools that can perform complex, multistep tasks on behalf of humans with minimal supervision. The idea with agentic AI is that it can boost productivity by taking care of the repetitive and laborious tasks that human workers would rather not do themselves. The new feature follows in the footsteps of Operator, which is a tool that's able to use a web browser to complete tasks such as finding and booking a hotel room. OpenAI showed off deep research's capabilities in a video embedded in its blog post, in relation to a request for information about how the retail industry has changed over the last three years. It provided a detailed response with various bullet points and tables. It also ran deep research through an AI benchmark called "Humanity's Last Exam", which rates AI models on their ability to respond to "expert-level questions". OpenAIU said it achieved a new record high score with 26.6% accuracy, which is far above ChatGPT's 3.3% score, and the o3-mini (high) model's 13% rating. The company said deep research is being launched for ChatGPT Pro users today, with up to 100 queries per month for users who pay the $200 monthly subscription fee. It's also promising to launch "limited access" for ChatGPT Plus, Team and Enterprise users in the coming weeks. There was no mention of deep research being made available to free users, which is likely because the model is "very compute intensive".

OpenAI launches deep research in ChatGPT: What is it and how it works

However, it can also help everyday users with tasks like comparing products before making a purchase. OpenAI has introduced a new feature in ChatGPT called deep research, designed to handle complex, multi-step online research. This advanced capability can analyse and summarise hundreds of online sources in a fraction of the time it would take a human. Keep reading for the details of OpenAI's new agent. Deep research is OpenAI's latest AI agent that works independently to conduct thorough research based on a user's query. According to OpenAI, "It accomplishes in tens of minutes what would take a human many hours." The feature is powered by a version of OpenAI's o3 model, optimised for web browsing and data analysis. Unlike regular ChatGPT responses, deep research digs through large amounts of data, including text, images, and PDFs available on the internet. It can also adjust its approach based on the information it finds, making it a powerful tool for those who need in-depth knowledge. According to OpenAI, deep research is built for finance, science, policy, and engineering professionals who require precise and reliable information. However, it can also help everyday users with tasks like comparing products before making a purchase. One of the standout features is its ability to find niche and non-intuitive information, often hidden across multiple sources. OpenAI explained in a blogpost, "every output is fully documented, with clear citations and a summary of its thinking, making it easy to reference and verify the information." "Deep research was trained using end-to-end reinforcement learning on hard browsing and reasoning tasks across a range of domains. Through that training, it learned to plan and execute a multi-step trajectory to find the data it needs, backtracking and reacting to real-time information where necessary," the company said. Users can access deep research in ChatGPT by selecting it in the message composer. After entering a query -- such as a competitive analysis on streaming platforms or a personalised report on the best commuter bike -- the tool starts working. A sidebar appears, showing the steps taken and sources used. The process can take anywhere from 5 to 30 minutes, after which the AI generates a detailed report. OpenAI says upcoming updates will include embedded images, data visualisations, and other analytic outputs for better clarity. OpenAI acknowledged that deep research still has some flaws. "It can sometimes hallucinate facts in responses or make incorrect inferences," the company admits, though it claims these errors are less frequent than with previous models. Also read: OpenAI faces legal heat in India, here's why For now, deep research is available only to ChatGPT Pro users, with a limit of 100 queries per month. OpenAI plans to roll it out next to Plus and Team users, followed by Enterprise customers. A faster, more cost-effective version of deep research is also in development.

OpenAI rolls out Deep research in ChatGPT for expert-level report generation

OpenAI has introduced a new feature called Deep Research in ChatGPT, designed to tackle complex, multi-step internet research tasks. This advanced capability enables ChatGPT to complete in "tens of minutes what would take a human many hours," according to the company. Deep Research is an autonomous agent that can independently search for, analyze, and synthesize hundreds of online sources to produce detailed, research analyst-level reports. Powered by a version of the upcoming OpenAI o3 model, it is optimized for web browsing and data analysis. The feature leverages advanced reasoning to interpret and analyze vast amounts of text, images, and PDFs while adapting its approach based on the information it encounters. OpenAI emphasizes that the ability to synthesize knowledge is a crucial step in the development of Artificial General Intelligence (AGI), which they envision as capable of producing novel scientific research. OpenAI developed Deep Research for professionals in fields such as finance, science, policy, and engineering, who need thorough, precise, and reliable research. It also serves consumers seeking hyper-personalized recommendations for purchases, such as cars, appliances, and furniture. Every output generated by Deep Research is fully documented, featuring clear citations and a summary of its reasoning, making it easy to verify. The tool excels at uncovering niche, non-intuitive information that would typically require extensive browsing. OpenAI highlights that Deep Research saves valuable time by handling complex, time-consuming research tasks with a single query. Deep Research was trained using end-to-end reinforcement learning on challenging browsing and reasoning tasks across multiple domains. It can plan and execute multi-step research trajectories, adjusting its approach as needed based on new information. The model can also browse user-uploaded files, plot graphs using Python, and embed images or graphs generated from websites into its responses. Furthermore, it cites specific sentences or passages from its sources, ensuring transparency. On Humanity's Last Exam, a rigorous evaluation testing AI across over 3,000 expert-level questions in more than 100 subjects, the model behind Deep Research achieved an impressive 26.6% accuracy. This score surpasses other models, such as GPT-4o (3.3%) and OpenAI's o3-mini (13%), marking significant improvements in subjects like chemistry, humanities, social sciences, and mathematics. It also set a new benchmark on the GAIA public leaderboard for real-world problem-solving, excelling in reasoning, web browsing, and tool-use proficiency. To use Deep Research in ChatGPT, simply select the 'Deep Research' option in the message composer and enter your query. Users can request anything from a competitive analysis of streaming platforms to a personalized report on the best commuter bike. You can also attach files or spreadsheets for added context. Once the process begins, a sidebar will display a summary of the steps taken and the sources used. Research typically takes between 5 to 30 minutes to complete, during which users can continue other tasks. Upon completion, the final report is delivered within the chat. OpenAI plans to add embedded images, data visualizations, and other analytical outputs in the coming weeks for enhanced clarity. While GPT-4 excels in real-time, multimodal conversations, Deep Research is better suited for multi-faceted, domain-specific inquiries that require depth and detail. For example, when asked, "What's the average retirement age for NFL kickers?", Deep Research provides a thorough analysis that includes statistical context, supporting examples, and factors influencing the longevity of kickers, rather than simply offering a single number. On GAIA, a public benchmark evaluating AI on real-world questions, Deep Research achieved state-of-the-art (SOTA) performance, topping the external leaderboard. It also demonstrated significant improvements in expert-level tasks, automating hours of manual research across various domains. Although Deep Research unlocks impressive capabilities, it does have some limitations. Occasionally, it may hallucinate facts or make incorrect inferences, although its error rate is lower than that of existing ChatGPT models. It can also struggle to differentiate between authoritative sources and unreliable information, and may not always convey uncertainty accurately. At launch, there may be minor formatting errors in reports and citations. OpenAI expects these issues to improve with time and usage. Deep Research is available on ChatGPT's web version and will be rolled out to mobile and desktop apps within the month. Due to its compute-intensive nature, access is currently limited to Pro users, with up to 100 queries per month. Looking ahead, OpenAI envisions integrating Deep Research with Operator, a feature that allows for real-world actions. This combination will enable ChatGPT to perform increasingly sophisticated tasks by blending asynchronous online research with real-world execution.

ChatGPT unveils new AI agent 'Deep Research' for complex web tasks: All you need to know

The latest feature of ChatGPT comes shortly after OpenAI introduced Google's Operator, which was showcased in December but isn't available to the public yet. OpenAI introduced its new agentic feature for ChatGPT, called Deep Research, during a YouTube livestream on February 2. OpenAI founder Sam Altman announced the launch on X (formerly Twitter), stating, "Today we launch deep research, our next agent....this is like a superpower; experts on demand..it can go use the internet, do complex research and reasoning, and give you back a report...it is really good, and can do tasks that would take hours/days and cost hundreds of dollars." The new feature can work independently to plan and carry out a series of steps to gather the necessary data, adjusting and responding to real-time information as needed, according to OpenAI. Also Read : Temptation Island: See premiere date, where to watch, concept, plot, host and production team It shows a summary of its process in a sidebar, including citations and a quick overview of the steps it took for reference. Companies like OpenAI are working on making generative AI tools more useful and valuable so people are willing to pay for them. They believe their AI can do the job of a research analyst by conducting deep research and providing helpful insights. Users can ask questions using text, images and other files like PDFs or spreadsheets for more context. It will take about five to 30 minutes to generate a response in the chat window. In future, it's expected to also include images and charts in the responses. OpenAI also mentions some limitations for deep research, including that it can sometimes "hallucinate" or create false information, have difficulty distinguishing between reliable sources and rumours, and struggle with assessing the certainty of its responses. But OpenAI claims that deep research can be performed at the level of a research analyst. OpenAI is offering up to 100 queries per month for users who pay the $200 monthly fee, with "limited access" for Plus, Team, and eventually Enterprise users. They explain that the service is "very compute intensive" and requires more processing power the longer it takes to complete research. It also mentions that all paid users will have higher query limits in the future when a faster and more cost-effective version becomes available. Also Read : The Righteous Gemstones Season 4: HBO show's premiere date, teaser, storyline and cast A press release reveals that the model behind deep research scored a new record for accuracy on an AI benchmark called "Humanity's Last Exam," which tests responses to expert-level questions. The deep research model achieved 26.6% accuracy with browsing and Python tools enabled, far surpassing GPT-4's 3.3% and the next closest model, o3-mini (high), which scored 13% with only text evaluation. 1. What is Deep Research by OpenAI? Deep Research is a feature that enables ChatGPT to independently conduct complex research tasks, offering detailed reports with citations and summaries. It uses text, images, and files like PDFs for context. 2. How can users access Deep Research and what are its limitations? Users can access Deep Research with a $200/month subscription for up to 100 queries. Limitations include occasional false information, difficulty distinguishing reliable sources, and challenges in assessing response certainty.

OpenAI's new Deep Research is the ChatGPT AI agent we've been waiting for - 3 reasons why I can't wait to use it

OpenAI just revealed Deep Research, a new agentic capability in ChatGPT that lets you use AI to compile factual information in minutes, completely opening up new ways to use the world's most popular chatbot. In the launch press release, OpenAI claims Deep Research "accomplishes in tens of minutes what would take a human many hours." Sounds a bit dystopian, right? It's a move closer to a world where we can replace human labor with artificial intelligence. I wouldn't blame you if the thought of AI compiling research papers and working as an analyst is a step too far, and at first glance, I wasn't even interested in covering this new functionality as it's heavily marketed towards businesses, rather than consumers. That was until I saw OpenAI's examples of Deep Research's capabilities in day-to-day tasks, and now I can't wait to get my hands on the new ChatGPT agent. Deep Research has initially launched for $200 a month ChatGPT Pro subscribers, but OpenAI says the new capability will come to ChatGPT Plus and Team users in the future. At the time of writing, there's no information on if, or when, Deep Research will become available for free tier users, although OpenAI does a good job at trickling down functionality over time. OpenAI's website says, "Deep research is OpenAI's next agent that can do work for you independently - you give it a prompt, and ChatGPT will find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst." Think of it as your very own analyst that can go off on its own and report back findings to you in just a few minutes. Whether you need a report on something as niche as the UK's Hummingbird population, or as per OpenAI's example, a research report on how the retail industry has transformed in the last three years, Deep Research has you covered. While the focus here is on compiling reports for businesses, medical research, and other professional use cases, it's OpenAI's three examples of what Deep Research can do for the average consumer that makes me incredibly excited to give the new functionality a try: This Deep Research example is probably my favorite of the three I'm going to discuss on this list. Do you always struggle to find movie names, songs, or any other random tidbits of information that should be easy to remember? Well, ChatGPT's Deep Research could become your go-to AI tool. Here, ChatGPT is given a rundown of a TV show with examples of a couple of episodes that the user can remember. One of the episodes has two men playing poker, two men getting locked in a room, and two men going to a butcher shop, with one bringing a gift of vodka. If you were to write this prompt to ChatGPT 4o, it would try to come back with the right answer, but more times than not it would miss the mark due to its lack of research. With Deep Research, not only is the AI agent able to find the exact TV episode you're referring to but also gives you a breakdown of the details. In this example, the TV show is Counterpart and the scenes are found in Season 1, Episode 4. Just the ability to break down your prompt and research enough information to not only find an answer but give in-depth detail is something that we wouldn't have thought possible just a few years ago. If you're anything like me, this Deep Research functionality might become your new favorite way to use ChatGPT, and it should mean you never struggle to find that name on the tip of your tongue again. TechRadar provides awesome shopping advice when it comes to tech, but there are times when my colleagues and I just don't have the expertise. Take finding the perfect snowboard for your next trip, for example, wouldn't it be great if you could ask AI to compile in-depth research to help make that purchasing decision a breeze based on your needs? Well, Deep Research can, and it's seriously impressive. In the example given, a quick prompt with information about a snowboard, slope conditions, and the area you'll be snowboarding on, leads to an impressive response that not only gives some of the best options but also goes into detail about why these options are worth exploring. The agent takes on board all of the user's requests and provides purchasing information that would otherwise take hours to compile yourself. Deep Research gives more in-depth answers that should be more reliable thanks to the heavy amount of research that goes into giving a response. OpenAI gives a great example of asking "What's the average retirement age for NFL kickers?" and showcases the difference between 4o and Deep Research with the results. 4o gives a sort of answer that deems the prompt too difficult to give an exact average. The model responds with a rough estimate of "between 35 and 40 years old", although compared to Deep Research's in-depth analysis it's nowhere near as conclusive. Deep Research, on the other hand, dives deep into multiple sources and compiles factual information to determine that NFL kickers can retire at multiple ages and explains the range of retirement ages with examples. It's a far more reliable answer and goes to show just how much Deep Research can improve responses when it comes to seeking answers using AI. While we don't know exactly when Deep Research will be available for those of us who don't pay for ChatGPT's most premium tier, these examples are enough to get me excited about the future of ChatGPT and what it's going to bring to the masses.

OpenAI Unveils Deep Research: A Game-Changer for AI-Powered Investigations

OpenAI Launches Deep Research to Enhance AI-Powered Information Gathering OpenAI Deep Research, a new artificial intelligence feature that applies ChatGPT. The system allows users to research different topics through extensive investigations, offering different functionality from typical chatbot functionality by analyzing multiple sources while delivering detailed results. OpenAI states that this tool provides significant advantages to professionals working in finance, science, policy and engineering industry sectors. The system helps buyers determine suitable choices when buying items such as cars, furniture and household appliances. Users who subscribe to can now access the new functionality, which allows 100 monthly queries. OpenAI planned to add deep research functionality first for its Plus and Team users and then for Enterprise customers. The geographical release targets specific regions, while the U.K., Switzerland, and the European Economic Area wait for undisclosed dates to receive the update.

OpenAI gives ChatGPT new deep research mode for complex web tasks

Why it matters: It's another step toward fulfillment of the AI industry's promise that AI agents will soon be able to perform human tasks reliably, efficiently and independently. What they're saying: "Deep research is built for people who do intensive knowledge work in areas like finance, science, policy, and engineering and need thorough, precise, and reliable research," OpenAI said in a blog post. "It can be equally useful for discerning shoppers looking for hyper-personalized recommendations on purchases that typically require careful research, like cars, appliances, and furniture." Yes, but: OpenAI also warns that deep research "can sometimes hallucinate facts in responses or make incorrect inferences," though it does so less than other ChatGPT models. Deep research will initially be made available to OpenAI's $200-a-month Pro customers. The big picture: The release of deep research follows fast on the heels of OpenAI's release of its Operator agent, which can act on behalf of users within a web browser to order products and reserve tickets.

OpenAI's 'Deep Research' Promises AI-Powered Analysis -- Here's What It Can (And Can't) Do - SoftBank Group (OTC:SFTBF), SoftBank Group (OTC:SFTBY)

On Sunday, OpenAI revealed a new feature for ChatGPT called "deep research," which autonomously plans and executes multi-step data searches. What Happened: This feature allows users to input questions using text, images, and files like PDFs or spreadsheets. It takes five to 30 minutes to generate a response but goes beyond text generation. The deep research feature displays a sidebar summary that outlines its research process, includes citations, and provides a reference overview. See Also: Tesla Reports Over 10% Employee Reduction By Year-End Following April Layoffs However, despite its capabilities, OpenAI acknowledges that deep research can sometimes "hallucinate" or confuse authoritative information with rumors. The tool is designed to operate at a research analyst level, but it is still refining its accuracy and reliability. OpenAI's deep research is available for Pro users, offering up to 100 queries per month for a $200 fee. Limited access is also available for Plus, Team, and Enterprise users. The model powering deep research achieved a 26.6% accuracy on an AI benchmark, surpassing previous models, said OpenAI. Subscribe to the Benzinga Tech Trends newsletter to get all the latest tech developments delivered to your inbox. Why It Matters: Last week, OpenAI launched the o3-mini model, which promises exceptional capabilities in science, math, and coding, while keeping costs low. This model is part of OpenAI's reasoning series and is available on both ChatGPT and the API. OpenAI's latest developments also include the debut of Operator, an AI agent capable of autonomously performing web tasks. This agent integrates GPT-4o's vision capabilities with advanced reasoning through reinforcement learning. Meanwhile, SoftBank Group Corp. SFTBF SFTBY is reportedly in talks to lead a new $40 billion funding round for OpenAI, which could value the company at $300 billion. Image via Shutterstock Check out more of Benzinga's Consumer Tech coverage by following this link. Read Next: Apple's iPad Turns 15 Today: Here's A Throwback To When Steve Jobs Explained Called It The 'Third Category' After Phones And Notebooks Disclaimer: This content was partially produced with the help of Benzinga Neuro and was reviewed and published by Benzinga editors. SFTBFSoftBank Group Corp$62.500.81%WatchlistOverviewSFTBYSoftBank Group Corp$30.50-0.62%Market News and Data brought to you by Benzinga APIs

ChatGPT's new 'Deep Research' tool promises analyst-level research reports in minutes

The tool is powered by the upcoming OpenAI o3 model with future plans for data visualizations and analytics. OpenAI has launched a new tool in ChatGPT to help users explore topics more deeply. Aptly named "Deep Research," the tool mirrors the functionality of Google Gemini's feature of the same name. OpenAI claims Deep Research in ChatGPT can accomplish in tens of minutes what would take a human many hours. Who's it for? Well, Deep Research is designed to help ChatGPT users who do intensive knowledge work. It can help write comprehensive reports based on data combined, analyzed, and synthesized from hundreds of online sources. The company promises that Deep Research can create reports "at the level of a research analyst." At the same time, users can also utilize the tool to personalize shopping recommendations for important purchases that typically require extensive research, such as buying cars, appliances, furniture, and more. "Powered by a version of the upcoming OpenAI o3 model that's optimized for web browsing and data analysis, it leverages reasoning to search, interpret, and analyze massive amounts of text, images, and PDFs on the internet, pivoting as needed in reaction to information it encounters," OpenAI explained. Deep Research will also provide citations for all its sources and a summary of its thinking, making it easier for users to verify the information. For now, Deep Research is available to ChatGPT Pro users. It will later be rolled out for ChatGPT Plus and Team users. To use the tool in ChatGPT, users would need to tap on "Deep Research" in the message composer and enter their query. Users can also attach spreadsheets or files to add context to their queries. Once Deep Research starts running, a sidebar appears with a summary of the steps taken and sources used will appear. OpenAI says the tool takes five to thirty minutes to complete its work. Users will receive a notification when the AI is done with its research. In the coming weeks, OpenAI will allow adding embedded images, data visualizations, and other analytic outputs to these reports for additional clarity and context.

OpenAI reveals new AI tool that can do online research for you

The artificial intelligence giant revealed another new feature from ChatGPT this week, called Deep Research, which it claims can gather research from across the web and summarize it in easy-to-read reports. "Deep research is OpenAI's next agent that can do work for you independently -- you give it a prompt, and ChatGPT will find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst," the company wrote in a Sunday blog post. Every output shows clear citations and a summary of the agent's thinking. The tool is powered by its upcoming OpenAI o3 model, which it says "leverages reasoning to search, interpret, and analyze massive amounts of text, images, and PDFs on the internet, pivoting as needed in reaction to information it encounters."

Here's How OpenAI's New 'Deep Research' Tool Could Change Your Workplace

In an FAQ page explaining what the tool can do, OpenAI explains it's "perfect for people who do intense knowledge work in areas like finance, science, and law," or "researchers and discerning shoppers who need thorough, precise, and reliable research." It's particularly good at "finding niche, non-intuitive information that would involve multiple steps across numerous websites," OpenAI suggests. It works like this: you ask the tool to look for information on a particular topic, adding images, files or extra data like PDFs or spreadsheets to add context and help explain your query, which could easily be useful in, say, a question about financial information. OpenAI says it will sometimes pop up a form to ask you specific information before it starts gathering data so it can create a "more focused and relevant" answer. The final report is "fully documented with clear citations to sources" so you can be certain that the information it's found is both relevant and correct -- allowing the important step of checking whether the AI has hallucinated the info, or if it's real. Speaking at an event in Washington D.C. to show off the new tool, OpenAI's chief product officer Kevin Weil made some bold claims about the tech, the New York Times reported. It'll be able to do "complex research tasks that might take a person anywhere from 30 minutes to 30 days," Weil said, adding that the tool will complete these tasks in maybe 5 to 30 minutes. It's also able to search recursively, meaning it can do a single search, then when that leads to other data sources it can look for those too.

ChatGPT's agent can now do deep research for you

In a press release, it says that the model powering deep research scored a new high for accuracy on an AI benchmark dubbed "Humanity's Last Exam," which asks for responses to expert-level questions. The OpenAI deep research model reached an accuracy of 26.6 percent, well above GPT-4o's 3.3 percent, and the next highest scorer, its o3-mini (high) model at 13 percent. This feature closely follows OpenAI's launch of Operator, a tool that can use a web browser to complete tasks for you, and is similar to the Project Mariner research prototype Google showed off in December. Google's tool is not available to the public yet, but deep research is launching "with a version optimized for Pro users today." OpenAI is offering up to 100 queries per month for those paying the $200 monthly fee and "limited access" promised for Plus, Team, and eventually, Enterprise users, calling the ability "very compute intensive," requiring more inference compute the longer it takes to research something.

OpenAI announces new 'deep research' tool for ChatGPT

TOKYO (AFP) - US tech giant OpenAI on Monday unveiled a ChatGPT tool called "deep research" ahead of high-level meetings in Tokyo, as China's DeepSeek chatbot heats up competition in the AI field. Artificial intelligence newcomer DeepSeek has sent Silicon Valley into a frenzy, with its high performance and supposed low cost prompting calls for US developers to go faster. OpenAI, whose ChatGPT fronted generative AI's emergence into public consciousness in 2022, said its new tool "accomplishes in tens of minutes what would take a human many hours". "Deep research is OpenAI's next agent that can do work for you independently -- you give it a prompt, and ChatGPT will find, analyse, and synthesise hundreds of online sources to create a comprehensive report at the level of a research analyst," it said in a statement. In a livestreamed video announcement, OpenAI researchers showed how the tool can synthesise web search data to help recommend ski equipment to buy for a snow holiday in Japan. OpenAI chief Sam Altman is in Tokyo to meet Japan's Prime Minister Shigeru Ishiba later Monday along with Masayoshi Son, head of Japanese tech investment behemoth SoftBank Group. SoftBank and OpenAI are part of the Stargate drive announced by US President Donald Trump to invest up to $500 billion in artificial intelligence infrastructure in the United States. Ishiba is expected to visit Washington to meet Trump for the leaders' first in-person meeting later this week. On Monday afternoon, Altman and Son will hold a forum in Tokyo with around 500 businesses at which they are expected to announce plans to boost Japan's AI infrastructure. The Nikkei business daily reported that this will include building AI data centres and power plants to run them, without specifying the scale of the investment required. Separately, Altman told the Nikkei he wants to develop "a new kind of hardware" using artificial intelligence in partnership with Apple's former chief design officer Jony Ive. But Altman indicated that it would take several years to unveil a prototype, the Nikkei said. Altman also told the newspaper that DeepSeek is "a good model" that highlights the serious competition for AI reasoning technology, but that its "capability level isn't new". DeepSeek's performance has sparked a wave of accusations that it has reverse-engineered the capabilities of leading US technology, such as the AI powering ChatGPT. Last week OpenAI warned that Chinese companies are actively attempting to replicate its advanced AI models, prompting closer cooperation with US authorities.

OpenAI announces new 'deep research' tool for ChatGPT

Tokyo (AFP) - US tech giant OpenAI on Monday unveiled a ChatGPT tool called "deep research" ahead of high-level meetings in Tokyo, as China's DeepSeek chatbot heats up competition in the AI field. Artificial intelligence newcomer DeepSeek has sent Silicon Valley into a frenzy, with its high performance and supposed low cost prompting calls for US developers to go faster. OpenAI, whose ChatGPT fronted generative AI's emergence into public consciousness in 2022, said its new tool "accomplishes in tens of minutes what would take a human many hours". "Deep research is OpenAI's next agent that can do work for you independently -- you give it a prompt, and ChatGPT will find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst," it said in a statement. In a livestreamed video announcement, OpenAI researchers showed how the tool can synthesise web search data to help recommend ski equipment to buy for a snow holiday in Japan. OpenAI chief Sam Altman is in Tokyo to meet Japan's Prime Minister Shigeru Ishiba later Monday along with Masayoshi Son, head of Japanese tech investment behemoth SoftBank Group. SoftBank and OpenAI are part of the Stargate drive announced by US President Donald Trump to invest up to $500 billion in artificial intelligence infrastructure in the United States. Ishiba is expected to visit Washington to meet Trump for the leaders' first in-person meeting later this week. 'New kind of hardware' On Monday afternoon, Altman and Son will hold a forum in Tokyo with around 500 businesses at which they are expected to announce plans to boost Japan's AI infrastructure. The Nikkei business daily reported that this will include building AI data centres and power plants to run them, without specifying the scale of the investment required. Separately, Altman told the Nikkei he wants to develop "a new kind of hardware" using artificial intelligence in partnership with Apple's former chief design officer Jony Ive. But Altman indicated that it would take several years to unveil a prototype, the Nikkei said. Altman also told the newspaper that DeepSeek is "a good model" that highlights the serious competition for AI reasoning technology, but that its "capability level isn't new". DeepSeek's performance has sparked a wave of accusations that it has reverse-engineered the capabilities of leading US technology, such as the AI powering ChatGPT. Last week OpenAI warned that Chinese companies are actively attempting to replicate its advanced AI models, prompting closer cooperation with US authorities.

OpenAI announces new 'deep research' tool for ChatGPT

US tech giant OpenAI on Monday unveiled a ChatGPT tool called "deep research" that can produce detailed reports, as China's DeepSeek chatbot heats up competition in the AI field. The company made the announcement in Tokyo, where OpenAI chief Sam Altman also trumpeted a new joint venture with tech investor SoftBank Group to offer advanced artificial intelligence services to businesses. Altman and SoftBank founder Masayoshi Son will meet the Japanese prime minister later on Monday and will reportedly announce plans to boost Japan's AI infrastructure. It comes as AI newcomer DeepSeek has sent Silicon Valley into a frenzy, with some calling its high performance and supposed low cost a wake-up call for US developers. OpenAI, whose ChatGPT led generative AI's emergence into public consciousness in 2022, said its new tool "accomplishes in tens of minutes what would take a human many hours". "You give it a prompt, and ChatGPT will find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst," the company said in a statement. On social media platform X Altman said that deep research, which paid "Pro" ChatGPT users can access 100 times a month, was "slow" and required a lot of computing power. But he was more bullish on stage at a business forum in Tokyo. "This is a system that I think can do -- this is just an estimate of mine -- but I think can do a single-digit percentage of all economically valuable tasks in the world," Altman said. Crystal ball SoftBank and OpenAI are part of the Stargate drive announced by US President Donald Trump to invest up to $500 billion in artificial intelligence infrastructure in the United States. Similar steps to build AI data centers and power plants in Japan could be announced when Altman and Son meet Prime Minister Shigeru Ishiba, the Nikkei newspaper said. Ishiba is also expected to visit Washington to meet Trump for the leaders' first in-person meeting later this week. At their event for businesses on Monday afternoon, Son announced a new joint venture equally split between the two companies. Holding a purple crystal ball, the Japanese tycoon outlined the services of a new AI product called Cristal, which can crunch firms' system data, reports, emails and meetings. A joint statement said SoftBank would "spend $3 billion annually to deploy OpenAI's solutions across its group companies". The venture "will serve as a springboard for introducing AI agents tailored to the unique needs of Japanese enterprises while setting a model for global adoption", it said. 'New kind of hardware' Separately, Altman told the Nikkei he wanted to develop "a new kind of hardware" using artificial intelligence in partnership with Apple's former chief design officer Jony Ive. But Altman indicated it would take several years to unveil a prototype, the Nikkei said. Altman also told the newspaper that DeepSeek is "a good model" that highlights the serious competition for AI reasoning technology, but that its "capability level isn't new". DeepSeek's performance has sparked a wave of accusations that it has reverse-engineered the capabilities of leading US technology, such as the AI powering ChatGPT. OpenAI warned last week that Chinese companies are actively attempting to replicate its advanced AI models, prompting closer cooperation with US authorities. While OpenAI has not confirmed Altman's next movements, media reports said he was expected to travel on Tuesday to Seoul. A spokesperson for South Korean IT conglomerate Kakao told AFP that they would on Tuesday announce their "collaboration with OpenAI" but did not confirm whether Altman would be there.

ChatGPT Is Trying to Be a Better Research Assistant

I Tried Replacing Todoist with ChatGPT Tasks -- Here's Why It Doesn't Work With the launch of Operator, despite it being not great in its current state, ChatGPT became more than just a chatbot. OpenAI wants to continue on the same pat, and the latest addition is a tool that can perform deep research. It's not exactly a new concept, OpenAI has a few reasons why it swears it's better. ChatGPT has just added a new tool called "deep research." This new feature, which is right now only available for the chatbot's ultra-expensive Pro tier, allows ChatGPT to go beyond simple text generation and act as an autonomous research assistant, capable of planning and executing multi-step research processes to gather information and provide detailed, cited summaries. Users can pose questions using text, images, and even upload documents like PDFs or spreadsheets. Deep research then takes over, spending anywhere from 5 to 30 minutes meticulously sifting through information, backtracking when necessary, and reacting to real-time data to formulate its response. The results are presented in the chat window, complete with a summary of its process and citations displayed in a sidebar. OpenAI claims that future iterations of the tool will also be able to embed images and charts within its responses -- right now it's just text. This is not exactly a new concept. Google's Gemini, for one, already has a feature called "deep research" and works relatively similarly. It searches through multiple sources and takes a few minutes to compile and prepare a detailed report/article for you based on the information contained within those sources. I've tried it out a few times and found that it works pretty well and it's relatively polished -- it conducts a multi-step research process where it looks through user reviews, references multiple websites (sometimes even How-To Geek), looks at YouTube videos, compares the data it finds, and synthesizes it all in a single report. Plus, it's available with Google's Gemini Advanced subscription, which is $20 a month compared to the crazy $200 a month ChatGPT Pro commands. OpenAI knows that it's technically late on rolling out a feature like this, and provides a few reasons why it thinks you should use this one instead of other chatbots. Rather than being a glorified website aggregator, OpenAI says its deep research feature is designed to perform at the level of a research analyst. A demo video released by the company showcases the tool's ability to analyze retail industry changes over the past three years, producing a response that includes bullet points and tables. This deep research feature uses OpenAI's reasoning models, while Gemini's uses regular, run-of-the-mill Gemini 1.5 Pro (it will probably switch to Gemini 2.0 Pro soon). OpenAI is also highlighting the deep research feature's performance on a benchmark called "Humanity's Last Exam," where it achieved an accuracy of 26.6 percent on expert-level questions when equipped with browsing and Python tools. This significantly outperforms other models, including GPT-4o, which scored only 3.3 percent on the same test. We'd need to see how much of an accuracy difference there is between a report prepared by ChatGPT and one prepared by Gemini. Even then, we don't think a feature worth 10 times as much will create a report 10 times better, at least for most things people might use it for, but we might be blown away. OpenAI is also mentioning that at least this initial version of the feature might suffer from issues. This includes the potential for hallucinations (fabricating facts), difficulty distinguishing between authoritative information and rumors, and challenges in assessing the certainty of its own responses. This is a general issue with AI that no one has managed to fully shake off, but chances are that it will get better with time. Still, if you're going to use this, it wouldn't hurt to double-check whether its output is accurate. Source: The Verge, TechCrunch

OpenAI takes on DeepSeek with Deep Research, a powerful AI agent

OpenAI has introduced "deep research," a new feature for ChatGPT designed to operate autonomously in gathering and analyzing information. Unlike standard chatbot responses, this tool follows a structured, multi-step process to locate and verify data, adjusting its approach in real time. Users can input text, images, PDFs, and spreadsheets for context. The AI then takes between 5 to 30 minutes to produce a response, displaying a summary of its process alongside citations.

OpenAI announces new 'deep research' tool for ChatGPT

US tech giant OpenAI on Monday unveiled a ChatGPT tool called "deep research" ahead of high-level meetings in Tokyo, as China's DeepSeek chatbot heats up competition in the AI field. "Deep research is OpenAI's next agent that can do work for you independently -- you give it a prompt, and ChatGPT will find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst," OpenAI said in a statement.